python-如何在openCV中识别不完整的矩形

我如何解决从图像中识别和提取矩形的问题,如下图所示.

请注意,我的矩形可能不完整,并且缺少一些边,而某些边可能是部分线.

谢谢 ！

解决方法:

可以使用morphological操作(例如eroding and dilating)来解决.这两个操作将有助于创建闭合的矩形.
之后,您可以使用page中的教程来检测简单的形状,例如矩形.

我实现了一个快速演示,该演示适用于您提供的图像.

main.py：

import cv2
import numpy as np
from shapeDetector import ShapeDetector
import imutils

img = cv2.imread('t.png')
kernel = np.ones((5,5),np.uint8)
erosion = cv2.erode(img,kernel,iterations = 10)
dilate = cv2.dilate(erosion,kernel,iterations = 10)

腐蚀会使所有线条变粗,因此要恢复正常宽度,我们需要在腐蚀后进行扩张.我建议对扩张操作进行一次评论,以了解侵蚀的工作原理,反之亦然.
此操作将像这样改变您的图像

我使用的检测算法期望在黑色背景上出现白线.
这就是为什么我们需要反转图像.

cv2.bitwise_not ( dilate, dilate )

之后,我们可以使用教程中的代码.

image = dilate
resized = imutils.resize(image, width=300)
ratio = image.shape[0] / float(resized.shape[0])

# convert the resized image to grayscale, blur it slightly,
# and threshold it
gray = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
thresh = cv2.threshold(blurred, 60, 255, cv2.THRESH_BINARY)[1]
#thresh = dilate
# find contours in the thresholded image and initialize the
# shape detector
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
    cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
sd = ShapeDetector()

# loop over the contours
for c in cnts:
    # compute the center of the contour, then detect the name of the
    # shape using only the contour
    M = cv2.moments(c)
    cX = int((M["m10"] / M["m00"]) * ratio)
    cY = int((M["m01"] / M["m00"]) * ratio)
    shape = sd.detect(c)

    # multiply the contour (x, y)-coordinates by the resize ratio,
    # then draw the contours and the name of the shape on the image
    c = c.astype("float")
    c *= ratio
    c = c.astype("int")
    cv2.drawContours(image, [c], -1, (0, 255, 0), 2)
    cv2.putText(image, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,
        0.5, (255, 255, 255), 2)

    # show the output image
    cv2.imshow("Image", image)
    cv2.waitKey(0)

shapeDetector.py：

# import the necessary packages
import cv2

class ShapeDetector:
    def __init__(self):
        pass

    def detect(self, c):
        # initialize the shape name and approximate the contour
        shape = "unidentified"
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.04 * peri, True)
        # if the shape is a triangle, it will have 3 vertices
        if len(approx) == 3:
            shape = "triangle"

        # if the shape has 4 vertices, it is either a square or
        # a rectangle
        elif len(approx) == 4:
            # compute the bounding box of the contour and use the
            # bounding box to compute the aspect ratio
            (x, y, w, h) = cv2.boundingRect(approx)
            ar = w / float(h)

            # a square will have an aspect ratio that is approximately
            # equal to one, otherwise, the shape is a rectangle
            shape = "square" if ar >= 0.95 and ar <= 1.05 else "rectangle"

        # if the shape is a pentagon, it will have 5 vertices
        elif len(approx) == 5:
            shape = "pentagon"

        # otherwise, we assume the shape is a circle
        else:
            shape = "circle"

        # return the name of the shape
        return shape

结果：

标签：image-segmentation,scikit-image,opencv,image-processing,python
来源： https://codeday.me/bug/20191111/2018997.html