Question

我目前正在研究一个确定轮廓区域的 opencv 项目。我试图制定一个适当的阈值并对其应用 cv2.findContours。但是，我发现当轮廓与图像的边界相交时，使用 cv2.contourArea 会大大低估该区域。如何解决这个问题？（请检查附加的图像，它在示例图像上显示了错误的结果）

import cv2
import numpy as np

def midpoint(ptA, ptB):
    return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

Input = cv2.imread("Thresh.png")
Thresh = cv2.cvtColor(Input,cv2.COLOR_BGR2GRAY)

contours, hierarchy = cv2.findContours(Thresh,  cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
minArea = 0
for cnt in contours:
    area = cv2.contourArea(cnt)
    print(area)
    if (area > minArea) :
        x,y,w,h = cv2.boundingRect(cnt)
        rect = cv2.minAreaRect(cnt)
        box = cv2.boxPoints(rect)
        box = np.int0(box)
        Input = cv2.drawContours(Input,[box],0,(255,0,0),2)
        (tl, tr, br, bl) = box
        (tltrX, tltrY) = midpoint(tl, tr)
        cv2.putText(Input, "{:1f}".format(area),
        (int(tltrX), int(tltrY)), cv2.FONT_HERSHEY_SIMPLEX,
        0.65, (0, 255, 0), 2)
        cv2.imshow('Input',Input)
cv2.waitKey(0)
cv2.destroyAllWindows()

Input threshold image Determined contours (bounding rectangle) with written contour areas on it

Opencv轮廓区域返回错误结果

0 个答案: