How to detect colored patches in an image using OpenCV?

Question

I am trying to detect if the picture(black and white sketch) is colored or not in the room conditions by a mobile camera.

I have been able to get this result

using following code

Mat dest = new Mat (sections[i].rows(),sections[i].cols(),CvType.CV_8UC3);
Mat hsv_image = new Mat (sections[i].rows(),sections[i].cols(),CvType.CV_8UC3);

Imgproc.cvtColor (sections[i],hsv_image,Imgproc.COLOR_BGR2HSV);

List <Mat> rgb = new List<Mat> ();
Core.split (hsv_image, rgb);
Imgproc.equalizeHist (rgb [1], rgb [2]);
Core.merge (rgb, sections[i]);
Imgproc.cvtColor (sections[i], dest, Imgproc.COLOR_HSV2BGR);

Core.split (dest, rgb);

How can I sucessfully find out if the image is colored or not. The color can be any and it has room conditions. Please help me on this as I am beginner to it.

Thanks

Answer 1

To process the colorful image in HSV color-space is a good direction. And I split the channels and find the S channel is great. Because S is Saturation(饱和度) of color.

Then threshold the S with thresh of 100, you will get this.

It will be easy to separate the colorful region in the threshed binary image.

---

As @Mark suggest, we can use adaptive thresh other than the fixed one. So, add THRESH_OTSU in the flags.

Core python code is presented as follow:

##(1) read into  bgr-space
img = cv2.imread("test.png")

##(2) convert to hsv-space, then split the channels
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h,s,v = cv2.split(hsv)

##(3) threshold the S channel using adaptive method(`THRESH_OTSU`)  
th, threshed = cv2.threshold(s, 100, 255, cv2.THRESH_OTSU|cv2.THRESH_BINARY)

##(4) print the thresh, and save the result
print("Thresh : {}".format(th))
cv2.imwrite("result.png", threshed)


## >>> Thresh : 85.0

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