假设您要在.pdf 表单上查找水平线,这里有一个简单的方法:
- 将图像转换为灰度和自适应阈值图像
- 构造特殊内核以仅检测水平线
- 执行形态转换
- 查找轮廓并在图像上绘制
使用此示例图片
转换为灰度和自适应阈值得到二值图像
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
然后我们用cv2.getStructuringElement() 创建一个内核并执行形态变换以隔离水平线
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (15,1))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
从这里我们可以使用cv2.HoughLinesP()来检测线条,但是由于我们已经对图像进行了预处理并隔离了水平线,所以我们可以找到轮廓并绘制结果
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, (36,255,12), 3)
完整代码
import cv2
image = cv2.imread('2.png')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (15,1))
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, (36,255,12), 3)
cv2.imshow('thresh', thresh)
cv2.imshow('detected_lines', detected_lines)
cv2.imshow('image', image)
cv2.waitKey()