本文介绍了如何检测给定图像中的所有矩形框的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我尝试使用阈值,轮廓边缘和应用轮廓检测​​来检测图像中的所有矩形,但无法检测到所有矩形.最终,我想到了使用 hough 转换来检测相同的内容,但是当我尝试检测图像中的线条时,我得到了所有的线条.我只需要检测图像中的矩形框.有人能帮我吗?我是opencv的新手.

I tried to detect all the rectangles in image using threshold, canny edge and applied contour detection but it was not able to detect all the rectangles. Finally, I thought of detect the same using hough transforms but when I tried to detect lines in image, I'm getting all the lines. I need to detect only rectangular boxes in the image. Can someone help me? I'm new to opencv.

输入图片

代码:

import cv2
import matplotlib.pyplot as plt
import numpy as np

img =  cv2.imread("demo-hand-written.png",-1)
#img = cv2.resize(img,(1280,720))
edges = cv2.Canny(img,180,200)
kernel = np.ones((2,2),np.uint8)
d = cv2.dilate(edges,kernel,iterations = 2)
e = cv2.erode(img,kernel,iterations = 2)
#ret, th = cv2.threshold(img, 220, 255, cv2.THRESH_BINARY_INV)

lines = cv2.HoughLinesP(edges,1,np.pi/180,30, maxLineGap=20,minLineLength=30)
for line in lines:
    #print(line)
    x1,y1,x2,y2 = line[0]
    cv2.line(img,(x1,y1),(x2,y2),(0,255,0),3)
cv2.imshow("image",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

推荐答案

您可以使用以下代码作为起点.

You can use below code as a starting point.

img =  cv2.imread('demo-hand-written.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

thresh_inv = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)[1]

# Blur the image
blur = cv2.GaussianBlur(thresh_inv,(1,1),0)

thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]

# find contours
contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[0]

mask = np.ones(img.shape[:2], dtype="uint8") * 255
for c in contours:
    # get the bounding rect
    x, y, w, h = cv2.boundingRect(c)
    if w*h>1000:
        cv2.rectangle(mask, (x, y), (x+w, y+h), (0, 0, 255), -1)

res_final = cv2.bitwise_and(img, img, mask=cv2.bitwise_not(mask))

cv2.imshow("boxes", mask)
cv2.imshow("final image", res_final)
cv2.waitKey(0)
cv2.destroyAllWindows()

输出:

图1 :在上图中检测到矩形框

Figure 1: Detected rectangular boxes in the above image

图2 :在原始图像中检测到矩形轮廓

Figure 2: Detected rectangular contours in the original image

这篇关于如何检测给定图像中的所有矩形框的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

08-30 22:35