如何使用OpenCV检测图像中的彩色色块? [英] How to detect colored patches in an image using OpenCV?
问题描述
我试图通过移动相机检测房间条件下的图片(黑白素描)是否有彩色。
I am trying to detect if the picture(black and white sketch) is colored or not in the room conditions by a mobile camera.
我能够得到这个结果
使用以下代码
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);
我如何成功找出图像是否有彩色。颜色可以是任何颜色,它有房间条件。请帮助我,因为我是初学者。
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.
谢谢
推荐答案
要处理中的彩色图像,HSV色彩空间
是个好方向。我拆分了频道,发现 S
频道很棒。因为 S
是颜色的饱和度(饱和度)
。
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.
然后以阈值<$阈值 S
c $ c> 100 ,你会得到这个。
Then threshold the S
with thresh of 100
, you will get this.
在脱粒的二进制图像中分离彩色区域很容易。
It will be easy to separate the colorful region in the threshed binary image.
正如@Mark建议的那样,我们可以使用除固定阈值之外的自适应阈值。因此,在标志中添加 THRESH_OTSU
。
As @Mark suggest, we can use adaptive thresh other than the fixed one. So, add THRESH_OTSU
in the flags.
核心python代码如下所示:
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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