改进HoughLines以进行水平线检测(Python，OpenCV) [英] Improve HoughLines for horizontal lines detect (Python, OpenCV)

问题描述

我有这个源图像:

我的目标是删除底线，同时保持字母/数字不变.

My goal is to remove the bottom line while keep the letters/numbers untouched.

这是我使用的代码:

import cv2
import numpy as np

img = cv2.imread('src.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

edges = cv2.Canny(gray,100,200,apertureSize = 5)

minLineLength = 0
maxLineGap = 19
lines = cv2.HoughLinesP(edges,1,np.pi/180,15,minLineLength,maxLineGap)
for x in range(0, len(lines)):
    for x1,y1,x2,y2 in lines[x]:
        cv2.line(img,(x1,y1),(x2,y2),(255,255,255),2)

cv2.imshow('hough',img)
cv2.waitKey(0)

我到目前为止获得的最佳结果是:

The best result I achieved by now is this:

如何进一步改善它以尽可能清洁图像? 例如，单词下的图像，点和(静止)线周围的所有碎片，我该如何去除它们?

How can I improve it more, to clean the image as much as possible ? For example, all the debris all around the image, points and (still) lines under the words, how can I remove them ?

谢谢.

OT:有没有一种方法可以创建一个跟踪栏来更改参数(apertureSize，minLineLength，maxLineGap等)以实时查看结果?

OT: is there a way to create a trackbar of this which change the parameters (apertureSize, minLineLength, maxLineGap, etc) to see results in real time ?

推荐答案

根据@Link的请求:

As per @Link 's request:

我在python中的经验有限，所以我不知道这段代码的线程安全性如何，但这应该向您展示在python OpenCV中创建跟踪栏的基础.

I have limited experience in python so I don't know how thread safe this code is, but this should show you the basics of creating trackbars in python OpenCV.

def onChange(pos):
    global img
    global gray
    global dst

    dst = np.copy(img)

    apertureSize = cv2.getTrackbarPos("ApertureSize", "Result")
    minLineLength = cv2.getTrackbarPos("LineLength", "Result")
    maxLineGap = cv2.getTrackbarPos("LineGap", "Result")

    # according to OpenCV, aperture size must be odd and between 3 and 7
    if apertureSize % 2 == 0:
        apertureSize += 1
    if apertureSize < 3:
        apertureSize = 3

    edges = cv2.Canny(gray,100,200,apertureSize = apertureSize)

    lines = cv2.HoughLinesP(edges,1,np.pi/180,15,minLineLength,maxLineGap)
    for x in range(0, len(lines)):
        for x1,y1,x2,y2 in lines[x]:
            cv2.line(dst,(x1,y1),(x2,y2),(255,255,255),2)

#Run Main
if __name__ == "__main__" :

    img = cv2.imread("image.png", -1)
    dst = np.copy(img)

    cv2.namedWindow("Result", cv2.WINDOW_NORMAL)

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

    #default values for trackbars
    defaultApertureSize = 5
    minLineLength = 0
    maxLineGap = 19

    # according to OpenCV, aperture size must be odd and between 3 and 7
    # the aperture size range is (0 - 6)
    cv2.createTrackbar("ApertureSize", "Result", defaultApertureSize, 6, onChange)

    # line length range is (0 - 10)
    cv2.createTrackbar("LineLength", "Result", minLineLength, 10, onChange)

    # line gap range is (0 - 19)
    cv2.createTrackbar("LineGap", "Result", maxLineGap, 19, onChange)

    while True:
        cv2.imshow("Result", dst)
        key = cv2.waitKey(1)
        if key == ord('q'):
            break

    cv2.destroyAllWindows()

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