opencv 边缘检测

# -*-encoding:utf-8-*-
import pytesseract
from PIL import Image
from PIL import ImageFilter
from PIL import ImageFont
from PIL import ImageDraw
import numpy as np
from PIL import Image

import cv2


def main():
    img = cv2.imread('handwriting.jpg', 0)
    # =================================边缘检测
    # Canny(image, threshold1, threshold2, edges=None, apertureSize=None, L2gradient=None)
    # 参数2、3表示最低、高阈值，
    edges = cv2.Canny(img, 30, 70)  # canny边缘检测

    # ================================= 阈值分割后再检测边缘，效果会更好：
    _, thresh = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    #Otsu阈值法(用与两种颜色的图片进行)
    # Otsu阈值明显由于固定阈值(0)，省去了不断尝试阈值判断效果好坏的过程。

    # _, thresh = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU )
    edges2 = cv2.Canny(thresh, 30, 120)


    cv2.imshow('thresh', thresh)
    cv2.imshow('edges', edges)
    cv2.imshow('edges2', edges2)
    cv2.waitKey(0)



if __name__ == '__main__':
    main()