需求描述:
对倾斜的图片进行矫正,返回倾斜角度和矫正后的图片。
解决方法:
1、各种角度点被投影到一个累加器阵列中,其中倾斜角度可以定义为在最大化对齐的搜索间隔内的投影角度。
2、以不同的角度旋转图像,并为每次迭代生成像素的直方图。
3、为了确定倾斜角度,比较峰值之间的最大差异,并使用这个倾斜角度,旋转图像来纠正倾斜。
#coding=utf-8
import cv2
import numpy as npdef rotate_image(image, angle):(h, w) = image.shape[: 2]center = (w // 2, h // 2)M = cv2.getRotationMatrix2D(center, angle, 1.0)corrected = cv2.warpAffine(image, M, (w, h), flags = cv2.INTER_CUBIC, \borderMode = cv2.BORDER_REPLICATE)return correcteddef determine_score(arr):histogram = np.sum(arr, axis = 2, dtype = float)score = np.sum((histogram[..., 1 :] - histogram[..., : -1]) ** 2, \axis = 1, dtype = float)return scoredef correct_skew(image, delta = 0.1, limit = 5):thresh = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY_INV + \cv2.THRESH_OTSU)[1]angles = np.arange(-limit, limit + delta, delta)img_stack = np.stack([rotate_image(thresh, angle) for angle \in angles], axis = 0)scores = determine_score(img_stack)best_angle = angles[np.argmax(scores)]corrected = rotate_image(image, best_angle)return best_angle, corrected
if __name__ == "__main__":file_path=r'D:/_21.png'img = cv2.imread(file_path, 0)angle, corrected = correct_skew(img)print(angle)cv2.imwrite(r'D:/temp_' + file_path.split('/')[-1], corrected)
执行结果:
矫正前:
矫正后: