OCR with javacv

Question

I am making an OCR for my project and stuck on a point, Right now i am performing segmentation on the basis of contours its working fine with few images but there few more where it fails even when the image quality is good, I would appreciate if someone suggest me more accurate way, and if someone provide a code example, here is my current code.

public static void imageBinarization(IplImage src, IplImage dst){
    IplImage r, g, b, s;
        r = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
        g = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
        b = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);

        cvSplit(src, r, g, b, null);

        s = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);

        cvAddWeighted(r, 1./3., g, 1./3., 0.0, s);
        cvAddWeighted(s, 2./3., b, 1./3., 0.0, s);
        cvThreshold(s, dst, 100, 100, CV_THRESH_BINARY_INV);
        cvReleaseImage(r);
        cvReleaseImage(g);
        cvReleaseImage(b);
        cvReleaseImage(s);
}
public static void imageSegmentation(String sourcePath, String targetPath){
    cvConvert(t0, mat0);
    cvConvert(t8, mat8);
    cvConvert(t9, mat9);

    IplImage image = cvLoadImage(sourcePath);
    IplImage grayImage = cvCreateImage(cvGetSize(image), IPL_DEPTH_8U, 1);

    //cvSmooth(image, image, CV_BLUR_NO_SCALE, 2);

    //cvSmooth(image, image, CV_BLUR, 9, 9, 2, 2);

    //cvSmooth(image, image, CV_GAUSSIAN, 3);

    imageBinarization(image, grayImage);



    CvMemStorage mem;
    CvSeq contours = new CvSeq();
    CvSeq ptr = new CvSeq();
    mem = cvCreateMemStorage(0);
    CvRect rect = null;
    int px1,px2, py1, py2;

    CvScalar blue = CV_RGB(0, 0, 250);
    int n = 0; int i = 0;
    cvFindContours(grayImage, mem, contours, sizeof(CvContour.class) , CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));

    Random rand = new Random();
    for (ptr = contours; ptr != null; ptr = ptr.h_next()) {

        Color randomColor = new Color(rand.nextFloat(), rand.nextFloat(), rand.nextFloat());
        CvScalar color = CV_RGB( randomColor.getRed(), randomColor.getGreen(), randomColor.getBlue());

        rect =  cvBoundingRect(ptr, n);//new CvRect(cvGetSeqElem(c, c.total()));
        px1 = rect.x(); py1 = rect.y(); px2 = (rect.x() + rect.width()); py2 = (rect.y() + rect.height());
        cvRectangle(image, cvPoint(px1, py1), cvPoint(px2, py2), blue, 1, CV_AA, 0);

        //----
        xbox = rect.x(); ybox = rect.y(); wbox = rect.width(); hbox = rect.height();
        img = cvCreateImage(cvSize(wbox, hbox), image.depth(), image.nChannels());
        cvSetImageROI(image, cvRect(xbox, ybox, wbox, hbox));
        cvCopy(image, img);
        cvResetImageROI(image);

        //cvSaveImage(targetPath+i+".jpg", img);
        i++;
        //---
        //cvDrawContours(image, ptr, color, CV_RGB(0,0,0), -1, CV_FILLED, 8, cvPoint(0,0));
    }
    cvSaveImage(targetPath+"mat.jpg", image);
}

Answer 1

Try to use some Global Thresholding algorithm such as Otsu. But JavaCV haven't implemented that. So try to find the Otsu threshold level using histogram processing and apply that value to

cvThreshold(s, dst, 100, 100, CV_THRESH_BINARY_INV);