{"id":12662,"date":"2024-03-15T16:56:10","date_gmt":"2024-03-15T07:56:10","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/opencv%e3%81%a7%e7%94%bb%e5%83%8f%e3%81%ae%e9%ab%98%e9%80%9f%e3%81%aa%e3%83%9e%e3%83%83%e3%83%81%e3%83%b3%e3%82%b0%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f\/"},"modified":"2025-08-05T13:30:52","modified_gmt":"2025-08-05T04:30:52","slug":"opencv%e3%81%a7%e7%94%bb%e5%83%8f%e3%81%ae%e9%ab%98%e9%80%9f%e3%81%aa%e3%83%9e%e3%83%83%e3%83%81%e3%83%b3%e3%82%b0%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/opencv%e3%81%a7%e7%94%bb%e5%83%8f%e3%81%ae%e9%ab%98%e9%80%9f%e3%81%aa%e3%83%9e%e3%83%83%e3%83%81%e3%83%b3%e3%82%b0%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f\/","title":{"rendered":"OpenCV\u3067\u753b\u50cf\u306e\u9ad8\u901f\u306a\u30de\u30c3\u30c1\u30f3\u30b0\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f"},"content":{"rendered":"

OpenCV\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u753b\u50cf\u306e\u7279\u5fb4\u3092\u691c\u51fa\u3057\u3001\u8a18\u8ff0\u3059\u308b\u65b9\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u753b\u50cf\u3092\u8fc5\u901f\u306b\u30de\u30c3\u30c1\u30f3\u30b0\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u57fa\u672c\u7684\u306a\u624b\u9806\u3067\u3059\u3002<\/p>\n

    \n
  1. \u753b\u50cf\u30922\u679a\u8aad\u307f\u8fbc\u3093\u3067\u3001\u305d\u308c\u3089\u3092\u767d\u9ed2\u753b\u50cf\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
    import<\/span> cv2\r\n\r\nimg1 = cv2.imread('image1.jpg'<\/span>)\r\nimg2 = cv2.imread('image2.jpg'<\/span>)\r\n\r\ngray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)\r\ngray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)\r\n<\/code><\/pre>\n
      \n
    1. SIFT\u3001SURF\u3001ORB\u306a\u3069\u306e\u7279\u5fb4\u691c\u51fa\u5668\u3068\u8a18\u8ff0\u5b50\u3092\u521d\u671f\u5316\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
      sift = cv2.SIFT_create()\r\n<\/code><\/pre>\n
        \n
      1. 2\u3064\u306e\u753b\u50cf\u3067\u7279\u5fb4\u70b9\u3092\u691c\u51fa\u3057\u3001\u8a18\u8ff0\u5b50\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
        keypoints1, descriptors1 = sift.detectAndCompute(gray1, None<\/span>)\r\nkeypoints2, descriptors2 = sift.detectAndCompute(gray2, None<\/span>)\r\n<\/code><\/pre>\n
          \n
        1. \u30de\u30c3\u30c1\u30e3\u30fc\u3092\u4f5c\u6210\u3057\u3001\u30c7\u30a3\u30b9\u30af\u30ea\u30d7\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u7279\u5fb4\u70b9\u3092\u30de\u30c3\u30c1\u30f3\u30b0\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
          bf = cv2.BFMatcher()\r\nmatches = bf.knnMatch(descriptors1, descriptors2, k=2<\/span>)\r\n<\/code><\/pre>\n
            \n
          1. \u9078\u629e\u3092\u884c\u3044\u3001\u512a\u308c\u305f\u30de\u30c3\u30c1\u30f3\u30b0\u30dd\u30a4\u30f3\u30c8\u3092\u6b8b\u3059\u3002<\/li>\n<\/ol>\n
            good_matches = []\r\nfor<\/span> m, n in<\/span> matches:\r\n    if<\/span> m.distance < 0.75<\/span> * n.distance:\r\n        good_matches.append(m)\r\n<\/code><\/pre>\n
              \n
            1. \u9078\u629e\u306b\u3088\u3063\u3066\u3001\u30de\u30c3\u30c1\u30f3\u30b0\u7d50\u679c\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
              matching_result = cv2.drawMatches(img1, keypoints1, img2, keypoints2, good_matches, None<\/span>, flags=2<\/span>)\r\ncv2.imshow('Matching Result'<\/span>, matching_result)\r\ncv2.waitKey(0<\/span>)\r\ncv2.destroyAllWindows()\r\n<\/code><\/pre>\n
              \u4e0a\u8a18\u306e\u624b\u9806\u306f\u5358\u7d14\u306a\u4f8b\u3067\u3042\u308a\u3001\u5177\u4f53\u7684\u306a\u7279\u5fb4\u691c\u51fa\u5668\u3084\u30de\u30c3\u30c1\u30f3\u30b0\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u9078\u629e\u304a\u3088\u3073\u8abf\u6574\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
              OpenCV\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u753b\u50cf\u306e\u7279\u5fb4\u3092\u691c\u51fa\u3057\u3001\u8a18\u8ff0\u3059\u308b\u65b9\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u753b\u50cf\u3092\u8fc5\u901f\u306b\u30de\u30c3\u30c1\u30f3\u30b0\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u57fa\u672c\u7684\u306a\u624b\u9806\u3067\u3059\u3002 \u753b\u50cf\u30922\u679a\u8aad\u307f\u8fbc\u3093\u3067\u3001\u305d\u308c\u3089\u3092\u767d\u9ed2\u753b\u50cf\u306b\u5909\u63db\u3057\u307e\u3059\u3002 import cv2 img1 […]<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[26,61],"class_list":["post-12662","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-26","tag-61"],"yoast_head":"\nOpenCV\u3067\u753b\u50cf\u306e\u9ad8\u901f\u306a\u30de\u30c3\u30c1\u30f3\u30b0\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f - 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