使用OpenCV改进图像中的矩形轮廓检测 [英] Improve rectangle contour detection in image using OpenCV

问题描述

我正在尝试检测给定图像中的矩形框

I am trying to detect the rectangular boxes in the given image

原始图片: 但是图像不足以检测矩形，如何改善图像并检测图像中的所有矩形?

Original image: but the image is not good enough to detect rectangles, how can i improve it and detect all the rectangles in image?

我尝试使用canny边缘检测并应用膨胀，双边过滤器将图像转换为二进制图像，然后输出如下:

I tried to convert the image into binary image using canny edge detection and applied dilation ,bilateral filter then the output is this:

我尝试应用所有morphologyEx，然后sobel无法检测到图像中的所有矩形.如果我能够找到矩形的所有边界，那么我可以使用findcountours来检测所有矩形，但是如何改善图像以检测所有矩形.

I tried to apply all the morphologyEx, sobel then to i was not able to detect all rectangles in the image. If i am able to find all the boundary of rectangle then i can detect all rectangles using find countours but how can i improve image to detect all the rectangles.

下面给出了给定转换的代码

The code for the given conversion is given below

img =  cv2.imread("givenimage.png",0)
img = cv2.resize(img,(1280,720))
edges = cv2.Canny(img,100,200)
kernal = np.ones((2,2),np.uint8)
dilation = cv2.dilate(edges, kernal , iterations=2)
bilateral = cv2.bilateralFilter(dilation,9,75,75)
contours, hireracy = cv2.findContours(bilateral,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for i,contour in enumerate(contours):
    approx = cv2.approxPolyDP(contour, 0.01*cv2.arcLength(contour,True),True)   
    if len(approx) ==4:
        X,Y,W,H = cv2.boundingRect(approx)
        aspectratio = float(W)/H
        if aspectratio >=1.2 :
            box = cv2.rectangle(img, (X,Y), (X+W,Y+H), (0,0,255), 2)
            cropped = img[Y: Y+H, X: X+W]
            cv2.drawContours(img, [approx], 0, (0,255,0),5)
            x = approx.ravel()[0]
            y = approx.ravel()[1]
            cv2.putText(img, "rectangle"+str(i), (x,y),cv2.FONT_HERSHEY_COMPLEX, 0.5, (0,255,0))
cv2.imshow("image",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

以下程序的输出仅检测8个矩形:

Output of the following program detects only 8 rectangles:

但是我需要检测图像中存在的所有矩形

but i need to detect all the rectangles present in the image

1)我可以为所有黑色像素增加图像的厚度吗?

1) Can I increase the thickness of the image for all the black pixels in this:

2)我可以扩大

推荐答案

这是一种简单的方法:

• 将图像转换为灰度和高斯模糊
• 执行Canny边缘检测
• 查找轮廓并绘制矩形

Canny边缘检测

结果

import cv2

image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (3, 3), 0)
canny = cv2.Canny(blurred, 120, 255, 1)

# Find contours
cnts = cv2.findContours(canny, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]

# Iterate thorugh contours and draw rectangles around contours
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)

cv2.imshow('canny', canny)
cv2.imshow('image', image)
cv2.imwrite('canny.png', canny)
cv2.imwrite('image.png', image)
cv2.waitKey(0)

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