OpenCV3計算機視覺 Python語言實現(5)

圖像特徵提取以及匹配

Harris角點檢測

import cv2import numpy as npimg = cv2.imread(empire.jpg)gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#得到正幅圖像的角點信息 dst為image.shape#第三個參數23為sobel運算元的中孔，定義了角點檢測的敏感度（3-31）dst = cv2.cornerHarris(gray,2,23,0.04)img[dst>0.01*dst.max()] = [0,0,255]cv2.imshow(corners,img)cv2.waitKey()

import cv2import numpy as npimage = cv2.imread(empire.jpg)gray_im = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)#創建sift提取對象sift = cv2.xfeatures2d.SIFT_create()#對灰度圖像提取sift特徵 keypoints為keypoint類型的列表#descriptor為每一個keypoint的128維描述符keypoints,descriptor = sift.detectAndCompute(gray_im,None)#在image圖像上繪製sift特徵點cv2.drawKeypoints(image,keypoints,image,(51,163,236),cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)cv2.imshow(sift_keypoints,image)cv2.waitKey()cv2.destroyAllWindows()

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