OpenCV 找到该图像的轮廓以进行裁剪和旋转

OpenCV find contour of this image to crop and rotate

我正在尝试检测此图像的轮廓以便在 openCV 中对其进行裁剪。

我已经想出了工作代码,但是,如果图像上有一些轻微的背景,它就会失败。

图像处理:

检测边界(蓝点):

Crop/rotate:

但是,对于像这样的图像,有一些背景光,它不起作用:

预处理:

边界检测:

def preProcessing(img):
    imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    adaptive_thresold1 = 31
    adaptive_thresold2 = 7

    blur = cv2.blur(imgGray, (3, 3))
    thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,adaptive_thresold1,adaptive_thresold2)

    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
    close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=2)

    stackedImages = hp.stackImages(0.1,([img,thresh, close],[img,thresh, close]))
    cv2.imshow("WorkFlow", stackedImages)
    cv2.waitKey(0) 
    return thresh


def getContours(img):
    biggest = np.array([])
    maxArea = 0
    img = cv2.bitwise_not(img)
    contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
    
    for cnt in contours:
        area = cv2.contourArea(cnt)
        if area>5000:
            print (area)
            
            #cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
            peri = cv2.arcLength(cnt,True)
            approx = cv2.approxPolyDP(cnt,0.02*peri,True)
            
            if area >maxArea and len(approx) == 4:
                biggest = approx
                maxArea = area
                print ("ok")
                
    print (biggest)
    out = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    cv2.drawContours(out, biggest, -1, (255, 0, 0), 50)

    stackedImages = hp.stackImages(0.1,([img,out],[img,out]))
    cv2.imshow("WorkFlow", stackedImages)
    cv2.waitKey(0)

    return biggest

有什么建议可以使此代码更可靠吗?

尝试使用 Otsu's thresholding

而不是使用自适应阈值

更改此行

thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,adaptive_thresold1,adaptive_thresold2)

在你的代码中 -

retval_blue, thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

这在图像中对我有用。