Android:使用JavaCV进行形状检测

时间:2016-12-07 08:28:47

标签: android opencv image-processing javacv edge-detection

我是JavaCV的新手。我试图检测图像中最大的矩形,并在原始图像上用颜色勾勒出轮廓。我发布了我尝试过的代码,但它无法正常工作。我正确地得到了edgeDetectedImage。我正好得到4个角点。只是cvDrawLine无效。如果我遗漏了任何内容,请提供帮助:

OnClick按钮我正在处理图片并在ImageView上再次显示。 在onClickListener按钮中:

if ((new File(path + "trial.jpg")).exists()) {
   opencv_core.IplImage originalImage = opencv_imgcodecs.cvLoadImage(path + "trial.jpg", opencv_imgcodecs.CV_IMWRITE_JPEG_QUALITY);
   opencv_core.IplImage iplImage = opencv_imgcodecs.cvLoadImage(path + "trial.jpg", opencv_imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
   opencv_core.IplImage edgeDetectedImage = applyCannyRectangleEdgeDetection(iplImage, 80);
   opencv_core.CvSeq largestContour = findLargestContour(edgeDetectedImage);
   opencv_core.CvPoint[] cvPoints = new opencv_core.CvPoint[4];
   for(int i=0; i<largestContour.total();i++)
   {
     opencv_core.CvPoint cvPoint = new opencv_core.CvPoint(cvGetSeqElem(largestContour, i));
     cvPoints[i] = cvPoint;
   }
   cvDrawLine(originalImage, cvPoints[0], cvPoints[1], opencv_core.CvScalar.YELLOW, 10, 10, 10);
   cvDrawLine(originalImage, cvPoints[1], cvPoints[2], opencv_core.CvScalar.YELLOW, 10, 10, 10);
   cvDrawLine(originalImage, cvPoints[2], cvPoints[3], opencv_core.CvScalar.YELLOW, 10,10, 10);
   cvDrawLine(originalImage, cvPoints[3], cvPoints[0], opencv_core.CvScalar.YELLOW, 10, 10,10);
   opencv_imgcodecs.cvSaveImage(path + "img1.jpg", originalImage);
                    if ((new File(path + "img1.jpg").exists())) {
                        imageView.setImageDrawable(Drawable.createFromPath(path + "img1.jpg"));
                    }
                }

方法applyCannyRectangleEdgeDetection(IplImage,int):

private opencv_core.IplImage applyCannyRectangleEdgeDetection(opencv_core.IplImage iplImage, int percent) {
    opencv_core.IplImage destImage = downScaleImage(iplImage, percent);
    OpenCVFrameConverter.ToMat converterToMat = new OpenCVFrameConverter.ToMat();
    Frame grayImageFrame = converterToMat.convert(destImage);
    opencv_core.Mat grayImageMat = converterToMat.convertToMat(grayImageFrame);
    GaussianBlur(grayImageMat, grayImageMat, new opencv_core.Size(5, 5), 0.0, 0.0, BORDER_DEFAULT);
    destImage = converterToMat.convertToIplImage(grayImageFrame);
    cvErode(destImage, destImage);
    cvDilate(destImage, destImage);
    cvCanny(destImage, destImage, 20, 55);
    return destImage;
}

方法downScaleImage(IplImage,int)

private opencv_core.IplImage downScaleImage(opencv_core.IplImage srcImage, int percent) {
    opencv_core.IplImage destImage = cvCreateImage(cvSize((srcImage.width() * percent) / 100, (srcImage.height() * percent) / 100), srcImage.depth(), srcImage.nChannels());
    cvResize(srcImage, destImage);
    return destImage;
}

方法findLargestContour(IplImage)

private opencv_core.CvSeq findLargestContour(opencv_core.IplImage edgeDetectedImage) {
    opencv_core.IplImage foundContoursOfImage = cvCloneImage(edgeDetectedImage);
    opencv_core.CvMemStorage memory = new opencv_core.CvMemStorage().create();
    opencv_core.CvSeq contours = new opencv_core.CvSeq();
    cvFindContours(foundContoursOfImage, memory, contours, Loader.sizeof(opencv_core.CvContour.class), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, new opencv_core.CvPoint(0, 0));
    int maxWidth = 0;
    int maxHeight = 0;
    opencv_core.CvRect contr = null;
    opencv_core.CvSeq seqFound = null;
    opencv_core.CvSeq nextSeq;
    for (nextSeq = contours; nextSeq != null; nextSeq = nextSeq.h_next()) {
        contr = cvBoundingRect(nextSeq, 0);
        if ((contr.width() >= maxWidth) && (contr.height() >= maxHeight)) {
            maxHeight = contr.height();
            maxWidth = contr.width();
            seqFound = nextSeq;
        }
    }
    opencv_core.CvSeq result = cvApproxPoly(seqFound, Loader.sizeof(opencv_core.CvContour.class), memory, CV_POLY_APPROX_DP, cvContourPerimeter(seqFound) * 0.1, 0);
    return result;
}

1 个答案:

答案 0 :(得分:0)

对不起,这应该是评论,但我没有足够的声誉。从代码中我可以看到,canny应用于缩小尺寸的图像,轮廓也是如此。您正在原始图像上绘制线条(未按百分比缩小),因此自然看起来不正确(如果看起来不正确但正在绘制某些内容)。否则,你应该提到图像的色彩空间,它与绘图无关,但对于canny而言。