Credit Card Recognition

Credit Card recognition will be based on the modal from OpenCV,  It's not necessary to train our own modal based on data as the card number format are mostly all the same.

1.  download the OpenCV jar file and add into classpath or import as maven, then static import the OpenCV c++ library as below:

static {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    }

2. read the credit card image into the program into the Mat object

public static void main(String[] args) {
        Mat srcImage = loadImage("img/card.jpg");
}

public static  Mat loadImage(String path) {
 Mat newImage = Imgcodecs.imread(path);
 return newImage;
}

3. turn the card image into grey color (grey scale process)

public static void main(String[] args) {
 Mat srcImage = loadImage("img/card.jpg");
 Mat grey = grey(srcImage);
}

public static Mat grey(Mat srcMat) {
 Mat dest = new Mat (); 
 Imgproc.cvtColor(srcMat, dest, Imgproc.COLOR_RGB2GRAY);
 return dest;
}

4. turn the grey scale image into a black & white image. (binary process)

public static void main(String[] args) 
{
 Mat srcImage = loadImage("img/card.jpg");
 Mat grey = grey(srcImage);
 Mat binary = blackWhite(grey);
}

public static Mat blackWhite(Mat grayMat) {
  Mat binaryMat = new Mat(grayMat.height(),grayMat.width(),CvType.CV_8UC1);
         Imgproc.threshold(grayMat, binaryMat, 30, 200, Imgproc.THRESH_BINARY);
         return binaryMat;
}

5. Erode the black & white image to make the word bolder and clearer so as to be easy to be recognized.

public static void main(String[] args) {
 Mat srcImage = loadImage("img/card.jpg"); 
 Mat grey = grey(srcImage);
        Mat binary = blackWhite(grey);
 Mat erode = imageErode(binary);
}
public static Mat imageErode(Mat srcMat) {
 Mat destMat = new Mat();
 Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3));
        Imgproc.erode(srcMat,destMat,element);
        return destMat;
}

6. crop the key region to remove the noise.

public static void main(String[] args) {
 Mat srcImage = loadImage("img/card.jpg");
 Mat grey = grey(srcImage);
        Mat binary = blackWhite(grey);
 Mat erode = imageErode(binary);
        Mat adjust = filterAndcut(erode);
}
public static Mat  filterAndcut(Mat destMat) {
  int a =0, b=0, state = 0;
         for (int y = 0; y < destMat.height(); y++) //row
         {
             int count = 0;
             for (int x = 0; x < destMat.width(); x++) //column
             {
                 // get the row pixel value 
                 byte[] data = new byte[1];
                 destMat.get(y, x, data);
                 if (data[0] == 0)
                     count = count + 1;
             }
             if (state == 0)//not a valid row
             {
                 if (count >= 150)//find a valid row
                 {//valid row qualify a 10 pixel noise
                     a = y;
                     state = 1;
                 }
             }
             else if (state == 1)
             {
                 if (count <= 150)// find a valid row
                 {//valid row qualify a 10 pixel noise
                     b = y;
                     state = 2;
                 }
             }
         }
         System.out.println("filter upper bound "+Integer.toString(a));
         System.out.println("filter lower bound "+Integer.toString(b));


         //crop the valid region
         Rect rect = new Rect(0,a,destMat.width(),b - a);
         Mat resMat = new Mat(destMat,rect);
         return resMat;
 }

7. recognize and print the result.

public static void main(String[] args) {
  Mat srcImage = loadImage("img/card.jpg");
  Mat grey = grey(srcImage); 
  Mat binary = blackWhite(grey);
  Mat erode = imageErode(binary);
  Mat adjust = filterAndcut(erode);
  
  printResult(matToBufferImage(adjust)); 
}

public static BufferedImage matToBufferImage(Mat grayMat) {
 if (grayMat == null) {
      return null;
 }
 byte[] data1 = new byte[grayMat.rows() * grayMat.cols() * (int)(grayMat.elemSize())];
 grayMat.get(0, 0, data1);
 BufferedImage image1 = new BufferedImage(grayMat.cols(), grayMat.rows(),BufferedImage.TYPE_BYTE_GRAY);                           
 image1.getRaster().setDataElements(0, 0, grayMat.cols(), grayMat.rows(), data1);
 return image1;
}

public static void printResult(BufferedImage src) {
 ITesseract instance = new Tesseract();
 instance.setDatapath("F:/Tess4J-3.4.8-src/Tess4J/tessdata"); // Credit card trained data
 long startTime = System.currentTimeMillis();
 String ocrResult;
 try {
       ocrResult = instance.doOCR(src);
       System.out.println("OCR Result: \n" + ocrResult + "\n spend：" + (System.currentTimeMillis() - startTime) + "ms");
 } catch (TesseractException e) {
       e.printStackTrace();
 } 
}

That's all for this project.