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I'm trying to detect skin in images using opencv (new to it), but I managed to get SOME part of the skin to be detected, but it all seems to create some noise in the image. Here's the original image:

original

The result of my code:

result

Code that prides itself on this:

Mat image = Imgcodecs.imread(name);

Imgproc.pyrMeanShiftFiltering(image, image, 10, 20);
Imgproc.blur(image, image, new Size(3, 3));

Mat hsv = new Mat();
Imgproc.cvtColor(image, hsv, Imgproc.COLOR_BGR2HSV);

Mat bw = new Mat();
Core.inRange(hsv, new Scalar(0, 10, 60), new Scalar(20, 150, 255), bw);

List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(bw, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_NONE, new Point(0, 0));
int s = findBiggestContour(contours);

Mat drawing = new Mat(image.size(), CvType.CV_8UC1);
Imgproc.drawContours(drawing, contours, s, new Scalar(255), -1, 8, hierarchy, 0, new Point(0, 0));

Imgcodecs.imwrite(rename(name), drawing);

How can I fix the code to detect the remaining skin in the image and get rid of the noise?

I am using Java with OpenCV 3.0.0.

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2 answers


Since you are using findBiggestConour()

I think you are hitting the greatest match, not all of them. Since the largest contour is the one shown in the second image.



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Just to add to what JanSLO said here above, I tried your code and instead of drawing only the largest outline, I drew all the outlines and got the following result.

//c++ code, not java
Mat drawing = Mat::zeros(img.size(), CV_8UC1 );
for(int i=0; i < contours.size(); ++i) {
    drawContours(drawing, contours, i, Scalar(255), 3, 8, hierarchy, 0, Point(0, 0));
}
imwrite("data/skin_detect_out.jpg", drawing);


skin_detect_out.jpg

I am pleasantly surprised with the result as it is such a simple piece of code. More advanced pixel-based detection techniques include creating a probabilistic model of skin pixels using training data and using that model to classify whether a given pixel is skin or not.

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