edge detection of a signature

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I have tried this code,actually this is a javacv code,

import javax.swing.JFrame; import com.googlecode.javacpp.Pointer; import com.googlecode.javacv.; import static com.googlecode.javacv.cpp.opencv_core.; import static com.googlecode.javacv.cpp.opencv_imgproc.; import static com.googlecode.javacv.cpp.opencv_highgui.;

public class SignatureDetector {

private static String SOURCE_FILE = "images\sourceImage.jpg"; private static String HOUGH_FILE = "images\houghrImage.jpg"; public static void main(String[] args) {

    String fileName = args.length >= 1 ? args[0] : "images\\Attendance_sheet.JPG"; // if no params provided, compute the defaut image
    IplImage src = cvLoadImage(fileName, 0);
    IplImage dst;
    IplImage colorDst;
    CvMemStorage storage = cvCreateMemStorage(0);
    CvSeq lines = new CvSeq();

    CanvasFrame source = new CanvasFrame("Source");
    CanvasFrame hough = new CanvasFrame("Hough");
    if (src == null) {
        System.out.println("Couldn't load source image.");
        return;
    }

    dst = cvCreateImage(cvGetSize(src), src.depth(), 1);
    colorDst = cvCreateImage(cvGetSize(src), src.depth(), 3);

    cvCanny(src, dst, 50, 200, 3);
    cvCvtColor(dst, colorDst, CV_GRAY2BGR);

    /*
     * apply the probabilistic hough transform
     * which returns for each line deteced two points ((x1, y1); (x2,y2))
     * defining the detected segment
     */
    if (args.length == 2 && args[1].contentEquals("probabilistic")) {
        System.out.println("Using the Probabilistic Hough Transform");
        lines = cvHoughLines2(dst, storage, CV_HOUGH_PROBABILISTIC, 1, Math.PI / 180, 40, 50, 10);
        for (int i = 0; i < lines.total(); i++) {
            // Based on JavaCPP, the equivalent of the C code:
            // CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
            // CvPoint first=line[0], second=line[1]
            // is:
            Pointer line = cvGetSeqElem(lines, i);
            CvPoint pt1  = new CvPoint(line).position(0);
            CvPoint pt2  = new CvPoint(line).position(1);

            System.out.println("Line spotted: ");
            System.out.println("\t pt1: " + pt1);
            System.out.println("\t pt2: " + pt2);
            cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0); // draw the segment on the image
        }
    }
    /*
     * Apply the multiscale hough transform which returns for each line two float parameters (rho, theta)
     * rho: distance from the origin of the image to the line
     * theta: angle between the x-axis and the normal line of the detected line
     */
    else if(args.length==2 && args[1].contentEquals("multiscale")){
                    System.out.println("Using the multiscale Hough Transform"); //
        lines = cvHoughLines2(dst, storage, CV_HOUGH_MULTI_SCALE, 1, Math.PI / 180, 40, 1, 1);
        for (int i = 0; i < lines.total(); i++) {
            CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));

            float rho=point.x();
            float theta=point.y();

            double a = Math.cos((double) theta), b = Math.sin((double) theta);
            double x0 = a * rho, y0 = b * rho;
            CvPoint pt1 = new CvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))), pt2 = new CvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));
            System.out.println("Line spoted: ");
            System.out.println("\t rho= " + rho);
            System.out.println("\t theta= " + theta);
            cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);
        }
    }
    /*
     * Default: apply the standard hough transform. Outputs: same as the multiscale output.
     */
    else {
        System.out.println("Using the Standard Hough Transform");
        lines = cvHoughLines2(dst, storage, CV_HOUGH_STANDARD, 1, Math.PI / 180, 90, 0, 0);
        for (int i = 0; i < lines.total(); i++) {
            CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));

            float rho ...