opencv+python实现图像矫正
本文实例为大家分享了opencv+python实现图像矫正的具体代码,供大家参考,具体内容如下
需求:将斜着拍摄的文本图像进行矫正
python代码
import numpy as np import cv2 as cv def shape_correction(img): (height, width) = img.shape[:2] print(img.shape) img_gau = cv.GaussianBlur(img, (5, 5), 0) canny = cv.Canny(img_gau, 60, 200) # cv.imshow("g-canny", canny) kernel = cv.getStructuringElement(cv.MORPH_CROSS, (4,3)) dilated = cv.dilate(canny, kernel, iterations=8) # cv.imshow('img_dilated', dilated) # 寻找轮廓 contours, hierarchy = cv.findContours(dilated, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE) # print(len(contours), hierarchy, sep='\n') # 找到最外层面积最大的轮廓 area = 0 # print("area:{}".format(area)) index = 0 for i in range(len(contours)): x, y, w, h = cv.boundingRect(contours[i]) # 排除非文本区域 if w < 35 and h < 35: continue # 防止矩形区域过大不精准 if h > 0.99 * height or w > 0.99 * width: continue # draw rectangle around contour on original image # cv.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2) tmpArea = w * h if tmpArea >= area: area = tmpArea index = i # 得到最小外接矩形的(中心(x,y), (宽,高), 旋转角度) rect = cv.minAreaRect(contours[index]) # 画出矩形框 # box = cv.boxPoints(rect) # box = np.int0(box) # cv.drawContours(img, [box], 0, (0, 0, 255), 2) # cv.imshow('img', img) print("rect:{}".format(rect)) angle = rect[-1] # print(angle) # 角度大于85度或小于5度不矫正 if angle > 85 or angle < 5: angle = 0 elif angle < 45: angle = angle - 0 else: angle = angle - 90 M = cv.getRotationMatrix2D(rect[0], angle, 1) rotated = cv.warpAffine(img, M, (width, height), flags=cv.INTER_CUBIC, borderValue=(255, 255, 255)) cv.imshow('Rotated', rotated) return rotated src = cv.imread('/res-normal.png', 0) rotated = shape_correction(src) cv.waitKey(0)
算法流程
算法核心思想:
获取图像中的文本区域矩形轮廓,找到其中面积最大的,对其进行最小外接矩形计算,得到最小外接矩形的旋转角度,再根据旋转角度进行仿射变换。
测试效果
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