python中opencv库的使用 (二) 霍夫直线检测与霍夫圆检测

悠悠 2022-10-02 01:47 223阅读 0赞

在图像处理中，经常会遇到对直线或者圆的检测，之后再进行后续处理，下面简单介绍一下opencv中的霍夫检测

对棋盘的直线检测

import cv2 as cv
    import numpy as np
    
    
    def line_detect(bw_image, image):
        # rho 线段以像素为单位的距离精度，double类型的，推荐用1.0
        # theta 检测直线的角度，一般为np.pi/180
        # threshold 直线上点数阈值，超过才会判断为直线，这里设为20
        # minLineLength 直线长度的阈值，超过才会判断为直线，这里设为20
        # minLineGap 不同线段之间的距离阈值，超过则默认为是一条直线，这里设为20
        lines = cv.HoughLinesP(bw_image, 1.0, np.pi/180, 20, minLineLength=20, maxLineGap=20)  # 霍夫变换检测直线
        for line in lines:
            line = line[0]
            x_start, y_start, x_end, y_end = line
            cv.line(image, (x_start, y_start), (x_end, y_end), (0, 255, 0), 3)
        cv.imshow('', image)
        cv.waitKey(0)
        cv.destroyAllWindows()
    
    if '__main__' == __name__:
        image_path = './chess.jpg'
        image = cv.imread(image_path)
        gray_image = cv.cvtColor(cv.imread(image_path), cv.COLOR_RGB2GRAY)
        ret, bw_image = cv.threshold(gray_image, 200, 255, cv.THRESH_BINARY_INV)
        line_detect(bw_image, image)

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTI2MDE2NDc_size_16_color_FFFFFF_t_70][]![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTI2MDE2NDc_size_16_color_FFFFFF_t_70 1][]

霍夫圆检测

import cv2 as cv
    import numpy as np
    
    def circle_detect(bw_image, image):
        # method   Hough 变换方式  HOUGH_GRADIENT
        # dp 直累加器图像的分辨率  一般为1
        # minDist 两个不同圆的最小距离
        # param1 用于处理边缘检测的梯度值方法
        # param2 累加器的阀值，阈值越小，检测到的圈子越多。
        # min_radius 最小圆半径
        # maxRadius 最大圆半径
        cv.imshow('', image)
        cv.waitKey(0)
        circles = cv.HoughCircles(bw_image, cv.HOUGH_GRADIENT, 1, 100, param1=100, param2=30, minRadius=20, maxRadius=500)
        for circle in circles[0]:
            x_center, y_center, radius = circle
            cv.circle(image, (x_center, y_center), radius, (0, 255, 0), 3)
        cv.imshow('', image)
        cv.waitKey(0)
        cv.destroyAllWindows()
    
    
    
    
    
    if '__main__' == __name__:
        image_path = './timg.jpg'
        image = cv.imread(image_path)
        gray_image = cv.cvtColor(cv.imread(image_path), cv.COLOR_RGB2GRAY)
        ret, bw_image = cv.threshold(gray_image, 20, 255, cv.THRESH_BINARY)
        circle_detect(bw_image, image)

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTI2MDE2NDc_size_16_color_FFFFFF_t_70 2][]![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTI2MDE2NDc_size_16_color_FFFFFF_t_70 3][]

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