I recently came across an article saying that barcodes and barcode readers have become a mainstay of today's economies and our lives in general, since they were introduced in the 1970s.
So, I decided to test how true this is by seeing how often I come across barcode readers in a typical day of mine. And — surprise surprise — they turned out to be more important than I thought.
A Reader's Day in My LifeRight after I left my home in the morning, I came across a bike for hire and used a bike sharing app to scan the QR code on the bike to unlock it. When I finally got to work, I scanned the bike's code again to lock it and complete the journey.
At lunch, I went to a café, sat down, and scanned the barcode on the table to order some lunch. After filling myself up, I went to the counter and scanned the QR code on the wall to pay.
And after work, before I went home, I went to my local collection point to pick up the smartwatch I'd recently bought. It was here where I saw the staff struggling to scan and record the details of the many packages they were handling. When I finally got home and had dinner, there was one last barcode to scan for the day. That was the QR code for the brand-new smartwatch, which was needed for linking the device with an app on my phone.
Overcoming Obstacles for Barcode ReadersThat said, scanning barcodes is not as easy as it sounds because the scanning experience encountered several challenges:
First, poor-quality barcodes made recognizing barcodes a challenge. Barcodes on the bike and table were smudged due to daily wear and tear, which is common in a public space.
Second, the placement of codes is not ideal. There was an awkward moment when I went to the counter to pay for my lunch, and the payment code was stuck on the wall right next to a person who thought I was trying to secretly take a picture of him.
Third is slow and rigid barcode scanning. When I went to the collection point, it was clear that the efficiency of the sorters was let down by their readers, which were unable to scan multiple barcodes at once.
Fourth, different barcode formats mean that the scanning mode must be switched.
So, in the face of all these challenges, I decided to develop my own reader. After doing some research and testing, I settled on HMS Core Scan Kit, because this kit utilizes computer vision technologies to ensure that it can recognize a hard-to-read barcode caused by factors including dirt, light reflection, and more. The kit can automatically zoom in on a barcode image from a distance so that the barcode can be easily identified, by using the deep learning algorithm model. The kit supports multi-scanning of five different barcodes at once, for faster recording of barcode information. And the kit supports 13 barcode formats, covering those commonly adopted in various scenarios.
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Aside from these advantages, I also found that the kit supports customization of the scanning UI, analysis of barcode content in 12 kinds of scenarios for extracting structured data, two SDKs (1.1 MB and 3.3 MB respectively), and four different call modes. An Android app can be integrated with the kit in just five lines of code. And of the modes available, I chose the Default View mode for my app. Let's have a look at how this works.
Service Process of the Solution
Specifically speaking:
1. A user opens an app and sends a barcode scanning request.
2. The app checks whether it has the camera permission.
3. When the app has obtained the permission, the app calls the startScan API to launch the barcode scanning UI.
4. The HMS Core SDK checks whether the UI is successfully displayed.
5. The HMS Core SDK calls onActivityResult to obtain the scanning result.
6. The app obtains the scanning result according to the scanning status (RESULT_CODE). If the result is SUCCESS, the app returns the scanning result to the user; if the result is ERROR_NO_READ_PERMISSION, the app needs to apply for the file read permission and enters the Default View mode again.
7. The app encapsulates the scanning result and sends it to the user.
Development ProcedureMaking Preparations1. Install Android Studio 3.6.1 or later.
2. Install JDK 1.8.211 or later.
3. Make the following app configurations:
minSdkVersion: 19 or later
targetSdkVersion: 33
compileSdkVersion: 31
Gradle version: 4.6 or later
4. Install the SDK Platform 21 or later.
5. Register as a developer.
6. Create a project and an app in AppGallery Connect.
7. Generate a signing certificate fingerprint, which is used to verify the authenticity of an app.
8. Go to AppGallery Connect to add the fingerprint in the SHA-256 certificate fingerprint field, as marked in the figure below.
9. Integrate the HMS Core SDK with the Android Studio project.
10. Configure obfuscation scripts so that the SDK will not be obfuscated.
11. Integrate Scan Kit via HMS Toolkit. For details, click here.
12. Declare necessary permissions in the AndroidManifest.xml file.
Developing the Scanning Function1. Set the scanning parameters, which is an optional step.
Scan Kit supports 13 barcode formats in total. You can add configurations so that Scan Kit will scan only the barcodes of your desired formats, increasing the scanning speed. For example, when only the QR code and DataMatrix code need to be scanned, follow the code below to construct the HmsScanAnalyzerOptions object.
When there is no specified format of the barcodes to be scanned, this object is not required. 1 is one of the parameter values for the scanning UI titles, corresponding to the var1 parameter in setViewType.
Code:
// QRCODE_SCAN_TYPE and DATAMATRIX_SCAN_TYPE indicate that Scan Kit will support only the barcodes in the QR code and DataMatrix formats. setViewType is used to set the scanning UI title. 0 is the default value, indicating title Scan QR code/barcode, and 1 indicates title Scan QR code. setErrorCheck is used to set the error listener. true indicates that the scanning UI is exited upon detection of an error; false indicates that the scanning UI is exited upon detection of the scanning result, without reporting the error.
HmsScanAnalyzerOptions options = new HmsScanAnalyzerOptions.Creator().setHmsScanTypes(HmsScan.QRCODE_SCAN_TYPE, HmsScan.DATAMATRIX_SCAN_TYPE).setViewType(1).setErrorCheck(true).create();
2. Call startScan of ScanUtil to start the scanning UI of the Default View mode, where a user can choose to use the camera to scan a barcode or go to the phone's album and select an image to scan.
REQUEST_CODE_SCAN_ONE: request ID, corresponding to the requestCode parameter of the onActivityResult method. This parameter is used to check whether the call to onActivityResult is from the scanning result callback of Scan Kit. If requestCode in the onActivityResult method is exactly the request ID defined here, the scanning result is successfully obtained from Scan Kit.
Set options to null when there is a need to scan barcodes in all formats supported by the kit.
Code:
ScanUtil.startScan(this, REQUEST_CODE_SCAN_ONE, options);
3. Receive the scanning result using the callback API, regardless of whether the scanned object is captured by the camera or from an image in the album.
Call the onActivityResult method of the activity to obtain the intent, in which the scanning result object HmsScan is encapsulated. RESULT describes how to obtain intent parameters.
If the value of requestCode is the same as that of REQUEST_CODE_SCAN_ONE defined in step 2, the received intent comes from Scan Kit.
Obtain the code scanning status through RESULT_CODE in the intent.
Use RESULT in the intent to obtain the object of the HmsScan class.
Code:
@Override
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
if (resultCode != RESULT_OK || data == null) {
return;
}
if (requestCode == REQUEST_CODE_SCAN_ONE) {
// Input an image for scanning and return the result.
int errorCode = data.getIntExtra(ScanUtil.RESULT_CODE, ScanUtil.SUCCESS);
if (errorCode == ScanUtil.SUCCESS) {
Object obj = data.getParcelableExtra(ScanUtil.RESULT);
if (obj != null) {
// Display the scanning result.
...
}
}
if (errorCode == ScanUtil.ERROR_NO_READ_PERMISSION) {
// The file read permission is not assigned. Apply for the permission.
...
}
}
}
Then — Boom! The barcode reader is all set and ready. I gave it a spin last week and everything seemed to be working well.
TakeawayBarcodes are everywhere these days, so it's important to carry a barcode reader at all times. This signals a fantastic opportunity for app developers.
The ideal barcode reader will support different barcode formats, be capable of identifying poor-quality barcodes in challenging environments, and support multi-scanning of barcodes at the same time.
As challenging as it sounds, HMS Core Scan Kit is the perfect companion. Computer vision techs, deep learning algorithm, support for multiple and continuous barcode scanning… With all these features, together with its easy-to-use and lightweight SDKs and flexible call modes, the kit gives developers and users all they'll ever need from a barcode reader app.
Related
This article is originally from HUAWEI Developer Forum.
Forum link: https://forums.developer.huawei.com/forumPortal/en/home
1 About This Document
Check out the machine learning service business introduction on the Huawei Developer website (https://developer.huawei.com/consumer/en/doc/development/HMS-Guides/ml-introduction-4)
It can be seen that Huawei HMS divides machine learning services into four major services: text-related services, language-related service, image-related services, and face/body-related services. One of them is text-related services. Including text recognition, document recognition, bank card recognition, general card recognition, what are the differences and associations between these sub-services?I will try to explain.
2 Application Scenario Differences
Text service SDKs are classified into device APIs and cloud APIs. Device APIs are processed and analyzed only on the device side and use the computing resource such as the CPU and GPU of the device. Cloud APIs need to send data to the cloud and use the server resources on the cloud for processing and analysis, all the services have device-side APIs except the document identification service, which requires a large amount of computing data to be processed on the cloud. To simplify the analysis scope, we only describe the device-side API service in this document.
2.1 Scenario Comparison
2.1.1 Text recognition: It is more like a versatile talent. Anything can be done, as long as it is text, it can be recognized.
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Text OCR application scenarios
Text OCR does not provide a UI. The UI is implemented by developers.
2.1.2 Bank card identification: more like a partial student, only a certain subject is excellent.
default customized box is provided for bank cards. You can quickly extract bank card numbers by directly aligning with the box.
Bank card identification
2.1.3 General cards: Between the above two categories, with certain attainments in a certain field. Can extract text from all cards. In addition, a card alignment box is provided to prompt users to align cards to be identified.
2.2 How to Choose
Bank Card OCR are selected for identification bank cards. For other types of cards, general cards identification are used for identification. For other scenarios, text recognition is used.
3 Service Integration Differences
Compilation Dependency Differences
In order to facilitate everyone's understanding, first explain the following concepts:
Basic SDK APIs provided for developers. All APIs are opened through the basic SDK.
Plug-in The calibration box mentioned in the previous scene comparison summary provides an interface to verify the input quality of the image frame. If it does not meet the requirements, can prompt the user to reposition it.
Model package This is the core of Huawei's HMS ML Kit services. It contains a large number of samples input through a machine learning platform to learn and generate interpreter model files.
Compilation Dependency Summary
According to the preceding compilation dependency, all services need to integrate the corresponding basic SDK and model package. However, Bank Card recognition, and General Card recognition have corresponding plug-ins, which are the calibration boxes mentioned above. In terms of models, Bank Card recognition use a dedicated model package, while General Card recognition and text recognition uses a general model package.
Development Differences
First, let's see how to integrate the services. The detailed steps are not described here. You can view the development steps of the corresponding services on Huawei Developers.
Text recognition
Create an identifier. MLTextAnalyzer analyzer = MLAnalyzerFactory.getInstance().getLocalTextAnalyzer(setting);
Create a fram object and transfer the image bitmap. MLFrame frame = MLFrame.fromBitmap(bitmap);
Send the frame object to the recognizer for recognition. Task<MLText> task = analyzer.asyncAnalyseFrame(frame);
Result handling Task<MLText> task = analyzer.asyncAnalyseFrame(frame); task.addOnSuccessListener(new OnSuccessListener<MLText>() { @override public void onSuccess(MLText text) { // Recognition success. } }).addOnFailureListener(new OnFailureListener() { @override public void onFailure(Exception e) { // Recognition failed. } });
Bank Card recognition
Start the UI to identify the bank card. private void startCaptureActivity(MLBcrCapture.Callback callback) {
Rewrite the callback function to process the recognition result. private MLBcrCapture.Callback callback = new MLBcrCapture.Callback() { @override public void onSuccess(MLBcrCaptureResult bankCardResult){ // Identify the success. } };
General Card recognition
Start the interface to identify the general card. private void startCaptureActivity(Object object, MLGcrCapture.Callback callback)
Rewrite the callback function to process the recognition result. private MLGcrCapture.Callback callback = new MLGcrCapture.Callback() { @override public int onResult(MLGcrCaptureResult cardResult){ //Successful identification processing The return MLGcrCaptureResult.CAPTURE_STOP;// processing is complete, and the identification is exited. } };
Development Summary
According to the preceding comparison, the processing logic is similar except that no GUI is provided for text recognition. The images to be recognized are transmitted to the SDK and the recognition result is obtained through the callback function. The core difference is that the returned structured data is different.
According to the preceding comparison, the bank card recognition return the directly processed identification content. You can directly obtain the bank card number through the interface without considering how the content is extracted. However, the text recognition and general card recognition return the full identification information, it contains text content such as blocks, lines, and words. If you want to obtain the required information, you need to extract the full information that is identified. For example, you can use the regular expression to match consecutive x digits to identify a card number or match the content after a recognized keyword.
4 Technical Difference Analysis
Based on the preceding difference analysis, we can see that text-related services are different in scenarios, service integration, also has some association. For example, Text recognition and General Card recognition use the same general machine learning model. The following analyzes and explains the technical differences from the technical perspective. As described in the compilation dependency analysis, the basic SDK and model package need to be integrated for text services, and plug-ins need to be integrated for some services to generate calibration boxes. What is the model package? You may be familiar with machine learning. Machine learning is usually divided into the collection of training samples, feature extraction, data modeling, prediction, etc. The model is actually a "mapping function" learned through training samples, feature extraction and other actions in machine learning. In HUAWEI HMS ML Kit, this mapping function is not enough. It needs to be executed, which is called the interpreter framework. In addition, some algorithms need to perform pre-processing and post-processing on the image, for example, converting an image frame into a corresponding eigenvector. To facilitate understanding, the preceding content is collectively referred to as a model file. To enable these model files to run on the mobile phone, the model files further need to be optimized, for example, a running speed of the model files on the mobile phone terminal is optimized, and a size of the model files is reduced.
Differences and association analysis
Now, let's look at the differences and relationships between text services. To facilitate understanding, the following figure shows the differences and relationships between text services.
Text recognition
The training is carried out using a general text data set. His advantages are wide application range and high flexibility. As long as the text content can be recognized.
General card recognition
It is the same as the data set used for text recognition, so there is no difference between the model files, but a general card plug-in is added. The main function is to ensure that the user points the card to the center of the camera, and also recognizes the reflective and blurred images , if the requirements are not met, the user is prompted to readjust, so that the recognition accuracy of the card can be improved.
Bank Card OCR
The bank card recognition service uses the dedicated data training set of the bank card. We all know that the characters on the bank card are greatly different from those in common print. In addition, the characters are convex. If the general model is used, it is difficult to achieve high accuracy, the training uses the dedicated data sets of bank cards and ID cards to improve the accuracy of ID card and bank card identification. In addition, targeted pre-processing is performed for bank cards. For example, the image quality and tilt angle can be dynamically detected in real time, and an alignment box can be generated to restrict the location of cards, if the image is blurred, reflected, or not aligned with the calibration box, the user is prompted to re-align the image.
Notice:
Based on Huawei machine learning service, we will share a series of practical experience later. You can continue to pay attention to our forum.
Any questions about this, you can try to acquire answers from HUAWEI Developer Forum.
More information like this, you can visit HUAWEI Developer Forum
Original link: https://forums.developer.huawei.com/forumPortal/en/topicview?tid=0201253487604250240&fid=0101187876626530001
1 About This Document
Check out the machine learning service business introduction on the Huawei Developer website
It can be seen that Huawei HMS divides machine learning services into four major services: text-related services, language-related service, image-related services, and face/body-related services. One of them is text-related services. Including text recognition, document recognition, bank card recognition, general card recognition, what are the differences and associations between these sub-services?I will try to explain.
2 Application Scenario Differences
First, let’s look at the sub-services of the text-related services and the scenario differences.
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Text service SDKs are classified into device APIs and cloud APIs. Device APIs are processed and analyzed only on the device side and use the computing resource such as the CPU and GPU of the device. Cloud APIs need to send data to the cloud and use the server resources on the cloud for processing and analysis, all the services have device-side APIs except the document identification service, which requires a large amount of computing data to be processed on the cloud. To simplify the analysis scope, we only describe the device-side API service in this document.
2.1 Scenario Comparison
As shown in the preceding table, the application scenarios of different capabilities are different.
2.1.1 Text recognition: It is more like a versatile talent. Anything can be done, as long as it is text, it can be recognized..
Text OCR application scenarios
Text OCR does not provide a UI. The UI is implemented by developers.
2.1.2 Bank card identification: more like a partial student, only a certain subject is excellent.
default customized box is provided for bank cards. You can quickly extract bank card numbers by directly aligning with the box.
Bank card identification
2.1.3 General cards: Between the above two categories, with certain attainments in a certain field. Can extract text from all cards. In addition, a card alignment box is provided to prompt users to align cards to be identified.
General card identification
2.2 How to Choose
Bank Card OCR are selected for identification bank cards. For other types of cards, general cards identification are used for identification. For other scenarios, text recognition is used.
3 Service Integration Differences
Compilation Dependency Differences
In order to facilitate everyone’s understanding, first explain the following concepts:
Basic SDK APIs provided for developers. All APIs are opened through the basic SDK.
Plug-in The calibration box mentioned in the previous scene comparison summary provides an interface to verify the input quality of the image frame. If it does not meet the requirements, can prompt the user to reposition it.
Model package This is the core of Huawei’s HMS ML Kit services. It contains a large number of samples input through a machine learning platform to learn and generate interpreter model files.
The following table summarizes the compilation dependencies of different services.
Compilation Dependency Summary
According to the preceding compilation dependency, all services need to integrate the corresponding basic SDK and model package. However, Bank Card recognition, and General Card recognition have corresponding plug-ins, which are the calibration boxes mentioned above. In terms of models, Bank Card recognition use a dedicated model package, while General Card recognition and text recognition uses a general model package.
Development Differences
First, let’s see how to integrate the services. The detailed steps are not described here. You can view the development steps of the corresponding services on the Developer website.
https://developer.huawei.com/consumer/en/doc/development/HMS-Guides/ml-introduction-4
The following describes the main development procedure of the corresponding service:
Text recognition
Create an identifier. MLTextAnalyzer analyzer = MLAnalyzerFactory.getInstance().getLocalTextAnalyzer(setting);
Create a fram object and transfer the image bitmap. MLFrame frame = MLFrame.fromBitmap(bitmap);
Send the frame object to the recognizer for recognition. Task<MLText> task = analyzer.asyncAnalyseFrame(frame);
Result handling Task<MLText> task = analyzer.asyncAnalyseFrame(frame); task.addOnSuccessListener(new OnSuccessListener<MLText>() { @override public void onSuccess(MLText text) { // Recognition success. } }).addOnFailureListener(new OnFailureListener() { @override public void onFailure(Exception e) { // Recognition failed. } });
Bank Card recognition
Start the UI to identify the bank card. private void startCaptureActivity(MLBcrCapture.Callback callback) {
Rewrite the callback function to process the recognition result. private MLBcrCapture.Callback callback = new MLBcrCapture.Callback() { @override public void onSuccess(MLBcrCaptureResult bankCardResult){ // Identify the success. } };
General Card recognition
Start the interface to identify the general card. private void startCaptureActivity(Object object, MLGcrCapture.Callback callback)
Rewrite the callback function to process the recognition result. private MLGcrCapture.Callback callback = new MLGcrCapture.Callback() { @override public int onResult(MLGcrCaptureResult cardResult){ //Successful identification processing The return MLGcrCaptureResult.CAPTURE_STOP;// processing is complete, and the identification is exited. } };
Development Summary
According to the preceding comparison, the processing logic is similar except that no GUI is provided for text recognition. The images to be recognized are transmitted to the SDK and the recognition result is obtained through the callback function. The core difference is that the returned structured data is different. To facilitate understanding, the following tables are provided:
Return the content summary.
According to the preceding comparison, the bank card recognition return the directly processed identification content. You can directly obtain the bank card number through the interface without considering how the content is extracted. However, the text recognition and general card recognition return the full identification information, it contains text content such as blocks, lines, and words. If you want to obtain the required information, you need to extract the full information that is identified. For example, you can use the regular expression to match consecutive x digits to identify a card number or match the content after a recognized keyword. Based on the preceding analysis, the development difficulty comparison is as follows:
Development difficulty comparison summary
4 Technical Difference Analysis
Based on the preceding difference analysis, we can see that text-related services are different in scenarios, service integration, also has some association. For example, Text recognition and General Card recognition use the same general machine learning model. The following analyzes and explains the technical differences from the technical perspective. As described in the compilation dependency analysis, the basic SDK and model package need to be integrated for text services, and plug-ins need to be integrated for some services to generate calibration boxes. What is the model package? You may be familiar with machine learning. Machine learning is usually divided into the collection of training samples, feature extraction, data modeling, prediction, etc. The model is actually a “mapping function” learned through training samples, feature extraction and other actions in machine learning. In HUAWEI HMS ML Kit, this mapping function is not enough. It needs to be executed, which is called the interpreter framework. In addition, some algorithms need to perform pre-processing and post-processing on the image, for example, converting an image frame into a corresponding eigenvector. To facilitate understanding, the preceding content is collectively referred to as a model file. To enable these model files to run on the mobile phone, the model files further need to be optimized, for example, a running speed of the model files on the mobile phone terminal is optimized, and a size of the model files is reduced.
Differences and association analysis
Now, let’s look at the differences and relationships between text services. To facilitate understanding, the following figure shows the differences and relationships between text services.
Text recognition integration mode
Text recognition
The training is carried out using a general text data set. His advantages are wide application range and high flexibility. As long as the text content can be recognized.
General card recognition
It is the same as the data set used for text recognition, so there is no difference between the model files, but a general card plug-in is added. The main function is to ensure that the user points the card to the center of the camera, and also recognizes the reflective and blurred images , if the requirements are not met, the user is prompted to readjust, so that the recognition accuracy of the card can be improved.
Bank Card OCR
The bank card recognition service uses the dedicated data training set of the bank card. We all know that the characters on the bank card are greatly different from those in common print. In addition, the characters are convex. If the general model is used, it is difficult to achieve high accuracy, the training uses the dedicated data sets of bank cards and ID cards to improve the accuracy of ID card and bank card identification. In addition, targeted pre-processing is performed for bank cards. For example, the image quality and tilt angle can be dynamically detected in real time, and an alignment box can be generated to restrict the location of cards, if the image is blurred, reflected, or not aligned with the calibration box, the user is prompted to re-align the image.
5 Summary
Based on the preceding analysis, the conclusion is as follows:
How, after reading this article, what feeling, come to express your opinion quickly!
DemoGithub address: https://github.com/HMS-MLKit/HUAWEI-HMS-MLKit-Sample
More information like this, you can visit HUAWEI Developer Forum
Introduction
The Huawei Scan Kit offers versatile scanning, decoding, and generation capacities for bar code and QR code, enabling developers to quickly create the scans for QR code in apps.
Huawei can automatically detect and amplify long-distance or smaller scan codes via its long-range accumulation in the computer vision sector and automate the recognition of normal, complex barcode (example: reflection) scanning (such as dark light, smudge, blur and cylinder) scanning services. Scan Kit improves the performance rate and user experience of QR scanning code.
Zxing is a common third-party open-source SDK, it allows an Android device with imaging hardware (a built-in camera) to scan barcodes or 2-D graphical barcodes and retrieve the data encoded. It only carries out simple QR-code scanning operations and does not support complex scanning conditions, including high light, bend and deformation. However, the optimization effect is still not ideal, and many people will spend a lot of time on the optimization.
Let us now evaluate the Zxing and the Huawei HMS scan kit capabilities:
Note
In this article, I have scanned the code for 5 times and taken the best time captured.
Results may vary from device to device. I have used Huawei Y7p device for scanning, maintained similar condition for both HMS scan and Zxing.
Normal Scanning
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When simple QR code is scanned from normal distance (around half feet), we have captured the time for decoding the code .
Huawei Scan kit took 0.68 seconds.
Zxing scanner took 1.38 seconds.
Result : HMS Scan kit wins
Scanning QR code at an angle
Let us scan the QR code at an angle more than 45 degrees from line of sight.
Huawei Scan kit took 0.657 seconds.
Zxing scanner took 1.27 seconds.
However, when we tried to capture at an angle more than 60 degrees, Zxing was not able to scan the code.
Result: HMS Scan kit wins
Scanning Complex Code:
Complex QR or bar code is too dense to decode. Let us see effectiveness of both the scanners.
Huawei scanner took 2.214 seconds when scanned from ideal distance (1.5 feet). However, if QR code is scanned from close distance it took 10.237 seconds. When QR code is scanned from distance more that 3 to 4 feet, it took 23.105 seconds.
ZXING scan took 19.10 seconds when scanned from ideal distance (1.5 feet). When scanned from too close or away from QR code, it was not able to able to scan it.
Result: HMS Scan kit wins.
Scanning code from long distance
Since Zxing does not have an automatic zoom-in optimisation, it is difficult to recognize code when the code is less than 20% of the frame.
The HMS Scan Kit has a pre-detection feature that can automatically amplify a long distance QR code even if the QR code cannot be detected by naked eyes.
HMS scan took 1.391 sec to detect when QR code is more 8 feet away.
Zxing failed to detect the code.
Result: HMS Scan kit wins
Implementation of HMS scan kit:
Prerequisite
Java JDK 1.8 or higher is recommended.
Android Studio is recommended.
Before developing an app, you will need to register as a HUAWEI developer. Refer to Register a HUAWEI ID.
Integrating app gallery connect SDK. Refer to AppGallery Connect Service Getting Started.
Development
1. Add the HMS scan kit dependencies in module-level build.gradle
Code:
implementation 'com.huawei.hms:scan:1.1.3.301'
2. To launch HMS default scanner
Code:
ScanUtil.startScan(this, REQUEST_CODE_SCAN_ONE, new HmsScanAnalyzerOptions.Creator().create());
3. Getting the scan result
Code:
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
if (resultCode != RESULT_OK || data == null) {
return;
}
endTime = System.currentTimeMillis();
//Default View
if (requestCode == REQUEST_CODE_SCAN_ONE) {
HmsScan obj = data.getParcelableExtra(ScanUtil.RESULT);
if (obj != null) {
tvTimer.setText(String.valueOf((endTime-startTime) /1 000) + " sec");
}
}
Implementation of Zxing scan:
1. Add the Zxing scan dependencies in module-level build.gradle
Code:
implementation 'com.journeyapps:zxing-android-embedded:3.4.0'
2. To initialize QR code scanner
Code:
qrScan = new IntentIntegrator(this);
3. To launch the scanner
Code:
//initiating the qr code scan
qrScan.initiateScan();
4. Getting the scan result
Code:
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
if (resultCode != RESULT_OK || data == null) {
return;
}
endTime = System.currentTimeMillis();
IntentResult result = IntentIntegrator.parseActivityResult(requestCode, resultCode, data);
tvTimer.setText(String.valueOf((endTime-startTime)/1000) + " sec");
if (result != null) {
//if qrcode has nothing in it
if (result.getContents() == null) {
Toast.makeText(this, "Result Not Found", Toast.LENGTH_LONG).show();
} else {
//if qr contains data
try {
//converting the data to json
JSONObject obj = new JSONObject(result.getContents());
} catch (JSONException e) {
e.printStackTrace();
}
}
}
}
}
Very nice and interesting article.
Just curious to know, If we scan in dark with mobile flash light, which takes less time?
In the mobile Internet era, people are increasingly using mobile apps for a variety of different purposes, such as buying products online, hailing taxis, and much more. When using such an app, a user usually needs to manually enter their address for package delivery or search for an appropriate pick-up and drop-off location when they hail a taxi, which can be inconvenient.
To improve user experience, many apps nowadays allow users to select a point on the map and then use the selected point as the location, for example, for package delivery or getting on or off a taxi. Each location has a longitude-latitude coordinate that pinpoints its position precisely on the map. However, longitude-latitude coordinates are simply a string of numbers and provide little information to the average user. It would therefore be useful if there was a tool which an app can use to convert longitude-latitude coordinates into human-readable addresses.
Fortunately, the reverse geocoding function in HMS Core Location Kit can obtain the nearest address to a selected point on the map based on the longitude and latitude of the point. Reverse geocoding is the process of converting a location as described by geographic coordinates (longitude and latitude) to a human-readable address or place name, which is much more useful information for users. It permits the identification of nearby street addresses, places, and subdivisions such as neighborhoods, counties, states, and countries.
Generally, the reverse geocoding function can be used to obtain the nearest address to the current location of a device, show the address or place name when a user taps on the map, find the address of a geographic location, and more. For example, with reverse geocoding, an e-commerce app can show users the detailed address of a selected point on the map in the app; a ride-hailing or takeout delivery app can show the detailed address of a point that a user selects by dragging the map in the app or tapping the point on the map in the app, so that the user can select the address as the pick-up address or takeout delivery address; and an express delivery app can utilize reverse geocoding to show the locations of delivery vehicles based on the passed longitude-latitude coordinates, and intuitively display delivery points and delivery routes to users.
Bolstered by a powerful address parsing capability, the reverse geocoding function in this kit can display addresses of locations in accordance with local address formats with an accuracy as high as 90%. In addition, it supports 79 languages and boasts a parsing latency as low as 200 milliseconds.
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DemoThe file below is a demo of the reverse geocoding function in this kit.
Preparations
Before getting started with the development, you will need to make the following preparations:
Register as a Huawei developer and complete identity verification on the HUAWEI Developers website. You can click here to find out the detailed registration and identity verification procedure.
Create a project and then create an app in the project in AppGallery Connect. Before doing so, you must have a Huawei developer account and complete identity verification.
Generate a signing certificate fingerprint and configure it in AppGallery Connect. The signing certificate fingerprint is used to verify the authenticity of an app. Before releasing an app, you must generate a signing certificate fingerprint locally based on the signing certificate and configure it in AppGallery Connect.
Integrate the Location SDK into your app. If you are using Android Studio, you can integrate the SDK via the Maven repository.
Here, I won't be describing how to generate and configure a signing certificate fingerprint and integrate the SDK. You can click here to learn about the detailed procedure.
Development Procedure
After making relevant preparations, you can perform the steps below to use the reverse geocoding service in your app. Before using the service, ensure that you have installed HMS Core (APK) on your device.
1. Create a geocoding service client.
In order to call geocoding APIs, you first need to create a GeocoderService instance in the onClick() method of GeocoderActivity in your project. The sample code is as follows:
Code:
Locale locale = new Locale("zh", "CN");
GeocoderService geocoderService = LocationServices.getGeocoderService(GeocoderActivity.this, locale);
2. Obtain the reverse geocoding information.
To empower your app to obtain the reverse geocoding information, you need to call the getFromLocation() method of the GeocoderService object in your app. This method will return a List<HWLocation> object containing the location information based on the set GetFromLocationRequest object.
a. Set reverse geocoding request parameters.
There are three request parameters in the GetFromLocationRequest object, which indicate the latitude, longitude, and maximum number of returned results respectively. The sample code is as follows:
Code:
// Parameter 1: latitude
// Parameter 2: longitude
// Parameter 3: maximum number of returned results
// Pass valid longitude-latitude coordinates. If the coordinates are invalid, no geographical information will be returned. Outside China, pass longitude-latitude coordinates located outside China and ensure that the coordinates are correct.
GetFromLocationRequest getFromLocationRequest = new GetFromLocationRequest(39.985071, 116.501717, 5);
b. Call the getFromLocation() method to obtain reverse geocoding information.
The obtained reverse geocoding information will be returned in a List<HWLocation> object. You can add listeners using the addOnSuccessListener() and addOnFailureListener() methods, and obtain the task execution result using the onSuccess() and onFailure() methods.
The sample code is as follows:
Code:
private void getReverseGeocoding() {
// Initialize the GeocoderService object.
if (geocoderService == null) {
geocoderService = new GeocoderService(this, new Locale("zh", "CN"));
}
geocoderService.getFromLocation(getFromLocationRequest)
.addOnSuccessListener(new OnSuccessListener<List<HWLocation>>() {
@Override
public void onSuccess(List<HWLocation> hwLocation) {
// TODO: Define callback for API call success.
if (null != hwLocation && hwLocation.size() > 0) {
Log.d(TAG, "hwLocation data set quantity: " + hwLocation.size());
Log.d(TAG, "CountryName: " + hwLocation.get(0).getCountryName());
Log.d(TAG, "City: " + hwLocation.get(0).getCity());
Log.d(TAG, "Street: " + hwLocation.get(0).getStreet());
}
}
})
.addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(Exception e) {
// TODO: Define callback for API call failure.
}
});
}
Congratulations, your app is now able to use the reverse geocoding function to obtain the address of a location based on its longitude and latitude.
Conclusion
The quick development and popularization of the mobile Internet has caused many changes to our daily lives. One such change is that more and more people are using mobile apps on a daily basis, for example, to buy daily necessities or hail a taxi. These tasks traditionally require users to manually enter the delivery address or pick-up and drop-off location addresses. Manually entering such addresses is inconvenient and prone to mistakes.
To solve this issue, many apps allow users to select a point on the in-app map as the delivery address or the address for getting on or off a taxi. However, the point on the map is usually expressed as a set of longitude-latitude coordinates, which most users will find hard to understand.
As described in this post, my app resolves this issue using the reverse geocoding function, which is proven a very effective way for obtaining human-readable addresses based on longitude-latitude coordinates. If you are looking for a solution to such issues, have a try to find out if this is what your app needs.
Question 1: I wanna know the privacy policy of Scan Kit and the data it collects. Where can I obtain such information?
Answer: Scan Kit's privacy policy and collected information are illustrated in its official "SDK Privacy and Security Statement" documents, which are separately specified for Android apps and iOS apps.
For Android apps, click here.
For iOS apps, click here.
Question 2: How to use Scan Kit so that my app can recognize multiple barcodes at the same time? If I adopt the multi-barcode recognition mode for my app, what should I do to make my app recognize specified barcodes? In this mode, can the coordinates of the recognized barcodes be returned by Scan Kit? Also, does this mode support auto zoom for a barcode?
Answer:
(1) To use Scan Kit for simultaneous multi-barcode recognition:
a. Use the MultiProcessor mode for an Android project.
b. Use the Bitmap mode for an iOS project.
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(2) To make an app recognize specified barcodes when the multi-barcode recognition mode is adopted:
You are advised to download the sample code of Scan Kit, debug it, and then modify it.
Specifically speaking, multi-barcode recognition is related to the following classes: MainActivity, CommonActivity, ScanResultView, CameraOperation, and CommonHandler. Modify them as follows:
Call cameraOperation.stopPreview(); to stop barcode scanning as soon as a barcode is successfully recognized.
Add the code for obtaining the coordinates of the screen position of a user's touch to CommonActivity.
Check whether the obtained coordinates are within the range defined by the coordinates of the HmsScan object returned by Scan Kit upon barcode recognition success. If so, the barcode scanning UI will be directed to your custom UI, and the HmsScan object will be passed to the custom UI.
You can submit a ticket online for more support, if the answer above does not resolve your question.
(3) Whether the coordinates of the recognized barcodes can be returned by Scan Kit or not:
Yes. The barcode scanning result is obtained via a barcode scanning request, and the result is in the HmsScan structure. You can call HmsScan.getBorderRect to obtain the coordinates of the recognized barcodes.
(4) Whether the multi-barcode recognition mode supports auto zoom for a barcode or not:
No. The multi-barcode recognition mode does not provide this function. This is to avoid the recognition effect of other barcodes being compromised. If you still want your app to provide the zoom-in/out function, you can implement it by using a button or via user touch.
Question 3: Does Scan Kit support auto zoom-in for barcodes? If yes, does the kit allow auto zoom-in to be canceled?
Answer: Scan Kit supports auto zoom-in, which is embedded in its Default View mode and Customized View mode. In either mode, auto zoom-in can be triggered when specific conditions are met, with zero additional configuration needed.
In Bitmap mode, when recognizing a barcode, Scan Kit would return a command for zoom ratio adjustment to your app. To know how, refer to step 4 in the Scanning Barcodes Using the Camera.
If you do not need the auto zoom-in function, you can select the MultiProcessor mode. It does not provide this function to prevent the recognition effect of other barcodes from being compromised.
Question 4: Does Scan Kit require any subscription fee or copyright authorization?
Answer: No and no. Scan Kit is free to use.
Question 5. How to implement continuous scanning with Scan Kit?
Answer:
Call ModeWhether Support Continuous ScanningHow to Implement Continuous ScanningExampleDefault View modeNo//Customized ViewYesCall setContinuouslyScan. When the value is true (default value), scanning results will be returned without interruption.
When the value is false, scanning results will only be returned one by one, and the same barcode will be returned only once.remoteView = new RemoteView.Builder().setContext(this).
setContinuouslyScan(true).build();Bitmap modeYesDo not close the camera during barcode scanning to obtain frames one by one. Then, send a barcode scanning request to Scan Kit. You can determine how the request is sent./MultiProcessor modeYes
As the above table shows, Customized View supports continuous barcode scanning. Specifically speaking, you need to set setContinuouslyScan (true) during initialization of RemoteView. For details, see the API Reference for RemoteView.Builder.
Note that the sample code has the logic to close the scanning UI once a barcode is successfully recognized. Therefore, if you use the sample code to test the continuous scanning function, remember to disable this logic in the success callback of RemoteView, to prevent the scanning process from being interrupted.
Question 6: How to customize the barcode scanning UI?
Answer: Barcode scanning UI customization is not supported by Default View but is supported by the Customized View, Bitmap, and MultiProcessor modes.
To know how to customize the UI, refer to the ScanResultView class and activity_defined.xml or activity_common.xml in the sample code of Scan Kit. You can make adjustments to the UI as required.
activity_defined.xml describes how to customize the UI in Customized View mode, and activity_common.xml tells how to customize the UI in Bitmap or MultiProcessor mode.
Question 7: How to obtain the following data of a successfully recognized barcode: barcode format, as well as the barcode image, barcode coordinates, and barcode corner point information?
Answer: The prerequisite for obtaining barcode information is that the corresponding barcode is recognized. Scan Kit returns all the information about the recognized barcode in an HmsScan object via the listener for the barcode scanning result callback.
The information covers the barcode coordinates in the input image, original barcode data, barcode format, structured data, zoom ratio, and more.
For details, see Parsing Barcodes and HmsScan.
Question 8: How to make Scan Kit automatically change the language of my app? What countries/regions are supported by the kit?
Answer: Scan Kit automatically changes the language for your app according to the system language settings, which does not require additional configuration.
Countries/Regions supported by the kit are displayed here. Their languages are also supported by the kit. The languages of countries/regions not listed in the link above means the languages are not yet supported by the kit.
Question 9: Does Scan Kit require the storage read permission when it needs to recognize a barcode in an image from the phone album? I found that in the Default View mode of Scan Kit, if this permission is not granted to the kit, it will fail to access an image from the phone album. Will this issue be resolved?
Answer: In SDK versions later than Scan SDK 2.10.0.301, the Default View mode allows the storage (media and files) read permission and camera permission to be acquired separately. Click here to learn how.
Get more information at:
HUAWEI Developer Forum
Home page of HMS Core Scan Kit
Development guide for HMS Core Scan Kit