问题描述

我正在尝试删除图像中存在的所有行。 我能够检测到线条，但当我试图删除线条时，我仍然在最终图像中得到几条小线条。我已经使用cv2.getStructuringElement获得了水平线和垂直线。在某些情况下，最终图像完全失真，我无法前进

图片来自Google

    res = verticle_lines_img + horizontal_lines_img 
    res = cv2.bitwise_not(res)
    fin=cv2.bitwise_or(img_bin, res,mask =cv2.bitwise_not(res))
    fin= cv2.bitwise_not(fin)
    exp =255-res
    final = cv2.bitwise_and(exp,img_bin)
    final = cv2.bitwise_not(final)
    exp = ~exp
    finalised = cv2.bitwise_and(img_bin,final)
    finalised = cv2.bitwise_not(finalised)

请帮帮我！谢谢

推荐答案

以下是一种方法

• 将图像转换为灰度
• 获取二值图像的大津阈值
• 删除水平线
• 删除垂直线

转换为灰度后，我们使用Otsu的阈值来获得二值图像

image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

从这里我们构造了一个特殊的水平核来检测水平线。一旦检测到行，我们就填入行以有效地删除行

# Remove horizontal
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10,1))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

类似地，为了删除竖线，我们构造了一个特殊的垂直内核

# Remove vertical
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,10))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, vertical_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

以下是检测到的绿色行

结果

您可以通过调整内核大小来微调结果。例如，将(10,1)更改为(15,1)将加强线条检测，而将其降低为(5,1)将放松检测

完整代码

import cv2

image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Remove horizontal
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10,1))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

# Remove vertical
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,10))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, vertical_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

cv2.imshow('thresh', thresh)
cv2.imshow('image', image)
cv2.waitKey()

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