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。
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)
我目前取得的最好成绩是这样的:
我怎样才能进一步改进它,以尽可能地清洁图像? 例如,图像周围的所有碎片、文字下方的点和(静止)线,如何去除它们?
谢谢。
OT:有没有办法创建一个跟踪栏来更改参数(apertureSize、minLineLength、maxLineGap 等)以实时查看结果?
最佳答案
根据@Link的请求:
我在 python 方面的经验有限,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 中创建轨迹栏的基础知识。
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()
关于python - 改进 HoughLines 以进行水平线检测(Python、OpenCV),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/46472713/