{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T19:48:56Z","timestamp":1723405736841},"reference-count":10,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2007,3,21]],"date-time":"2007-03-21T00:00:00Z","timestamp":1174435200000},"content-version":"vor","delay-in-days":5558,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems &amp;amp; Computers in Japan"],"published-print":{"date-parts":[[1992,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Template matching is a useful technique for matching images. This paper proposes a high\u2010speed template matching technique which is effective for images that have sharp contours. The method uses only the image contour parts as one\u2010dimensional templates. Although it can retain fine patterns, the data compression ratio and speed are very high. To improve reliability of matching, gray gradient information and intensity of contour points are used. Also, dilation of contours can reduce several errors due to disturbance of the contour or scaling. The algorithm herein can indicate differences between the template and the target image automatically after the alignment of images.<\/jats:p><jats:p>The expanded algorithm applying the sequential similarity detection algorithm (SSDA) method also is discussed. Software simulation proved that the algorithm is 10 or 200 times faster than the conventional template matching technique which uses the cross\u2010correlation estimation between two\u2010dimensional (2\u2010D) template and the target image. This algorithm was applied to special hardware. It can align two 512 \u00d7 512 pixels images in 40 ms when the size of the search area is 64 \u00d7 64.<\/jats:p>","DOI":"10.1002\/scj.4690230908","type":"journal-article","created":{"date-parts":[[2007,7,8]],"date-time":"2007-07-08T00:14:03Z","timestamp":1183853643000},"page":"78-87","source":"Crossref","is-referenced-by-count":7,"title":["High\u2010speed template matching algorithm using information of contour points"],"prefix":"10.1002","volume":"23","author":[{"given":"Manabu","family":"Hashimoto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuhiko","family":"Sumi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshikazu","family":"Sakaue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinjiro","family":"Kawato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2007,3,21]]},"reference":[{"key":"e_1_2_1_2_2","first-page":"10","article-title":"Digital Picture Processing","volume":"2","author":"Rosenfeld A.","year":"1982","journal-title":"Second edition"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1972.5008923"},{"key":"e_1_2_1_4_2","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1109\/TSMC.1977.4309663","article-title":"Coarse\u2010fine template matching","volume":"7","author":"Rosenfeld A.","year":"1977","journal-title":"IEEE Trans. Syst., Man & Cybern."},{"key":"e_1_2_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1977.1674847"},{"key":"e_1_2_1_6_2","doi-asserted-by":"crossref","unstructured":"K.Sumi N.NakajimaandY.Sakaue.Automated inspection vision using gray\u2010level image. Proc. IECON'87 856 pp.745\u2013751(1987).","DOI":"10.1117\/12.943037"},{"key":"e_1_2_1_7_2","unstructured":"A.MargalitandA.Rosenfeld.Reducing the expected computational cost of template matching using run length representation. Technical Report CFAR Univ. of MD CAR\u2010TR\u2010406 (1988)."},{"key":"e_1_2_1_8_2","article-title":"Fast Image Difference Detection by Edge\u2010Point Template Matching","volume":"90","author":"Hashimoto","year":"1990","journal-title":"I.E.I.C.E., Japan, Technical Reports"},{"key":"e_1_2_1_9_2","first-page":"2033","article-title":"Fast Gray\u2010Level Image Processing using Edge Characteristics","volume":"4","author":"Nakajima","year":"1987","journal-title":"Papers of 35th Plenary Session of Information Processing Society"},{"issue":"6","key":"e_1_2_1_10_2","first-page":"832","article-title":"Feature Extraction from Physiographic Maps by a Parallel Orientation Field Algorithm","volume":"31","author":"Yamada","year":"1990","journal-title":"Journal of the Image Processing Society"},{"key":"e_1_2_1_11_2","volume-title":"Image Processing Subroutine Package","author":"Institute of Electronic Technology.","year":"1980"}],"container-title":["Systems and Computers in Japan"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fscj.4690230908","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/scj.4690230908","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T14:03:53Z","timestamp":1698069833000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/scj.4690230908"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1992,1]]},"references-count":10,"journal-issue":{"issue":"9","published-print":{"date-parts":[[1992,1]]}},"alternative-id":["10.1002\/scj.4690230908"],"URL":"https:\/\/doi.org\/10.1002\/scj.4690230908","archive":["Portico"],"relation":{},"ISSN":["0882-1666","1520-684X"],"issn-type":[{"value":"0882-1666","type":"print"},{"value":"1520-684X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1992,1]]}}}