有没有办法从图像中提取扭曲的矩形/正方形？答案

【问题标题】：Is there any way to extract distorted rectangle/square from the image?有没有办法从图像中提取扭曲的矩形/正方形？
【发布时间】：2023-04-04 01:40:01
【问题描述】：

这是图像，我想填充这个矩形或正方形的边缘，以便我可以使用轮廓对其进行裁剪。到目前为止，我所做的是我使用精明的边缘检测器来查找边缘，然后使用 bitwise_or 我让这个矩形填充了一点但不完全。如何填充这个矩形或者有什么方法可以直接裁剪它？

image = cv2.imread('C:/Users/hp/Desktop/segmentation/test3.jpeg')

img3 = img2 = image.copy()
image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
img3 = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)

lower = np.array([155,25,0])
upper = np.array([179,255,255])
mask = cv2.inRange(image, lower, upper)

edges = cv2.Canny(mask, 1, 255, apertureSize=7)
result = cv2.bitwise_or(edges, mask)

【问题讨论】：

使用霍夫线变换得到沿精明边缘的线。然后找到他们的交点以获得 4 个角。然后绘制一个填充的多边形或获取4个角的边界框并裁剪图像。

标签： python image opencv image-processing cv2

【解决方案1】：

这是在 Python/OpenCV 中提取矩形白色像素边界的一种方法。

读取输入
转换为灰色
阈值
进行 Canny 边缘检测
获取霍夫线段并在黑色背景上绘制为白色
获取白色像素的边界
将输入裁剪到边界

输入：

import cv2
import numpy as np

# load image as grayscale
img = cv2.imread('rect_lines.jpg')

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold 
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY)[1]

# apply canny edge detection
edges = cv2.Canny(thresh, 100, 200)

# get hough line segments
threshold = 100
minLineLength = 50
maxLineGap = 20
lines = cv2.HoughLinesP(thresh, 1, np.pi/360, threshold, minLineLength, maxLineGap)

# draw lines
linear = np.zeros_like(thresh)
for [line] in lines:
    #print(line)
    x1 = line[0]
    y1 = line[1]
    x2 = line[2]
    y2 = line[3]
    cv2.line(linear, (x1,y1), (x2,y2), (255), 1)

# get bounds of white pixels
white = np.where(linear==255)
xmin, ymin, xmax, ymax = np.min(white[1]), np.min(white[0]), np.max(white[1]), np.max(white[0])
#print(xmin,xmax,ymin,ymax)

# draw bounding box on input
bounds = img.copy()
cv2.rectangle(bounds, (xmin,ymin), (xmax,ymax), (0,0,255))

# crop the image at the bounds
crop = img[ymin:ymax, xmin:xmax]

# save resulting masked image
cv2.imwrite('rect_lines_edges.png', edges)
cv2.imwrite('rect_lines_hough.png', linear)
cv2.imwrite('rect_lines_bounds.png', bounds)
cv2.imwrite('rect_lines_crop.png', crop)

# display result, though it won't show transparency
cv2.imshow("thresh", thresh)
cv2.imshow("edges", edges)
cv2.imshow("lines", linear)
cv2.imshow("bounds", bounds)
cv2.imshow("crop", crop)
cv2.waitKey(0)
cv2.destroyAllWindows()

精明的边缘：

霍夫线段：

输入框：

裁剪图像：

【讨论】：