{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T14:45:56Z","timestamp":1698417956791},"reference-count":12,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2007,3,21]],"date-time":"2007-03-21T00:00:00Z","timestamp":1174435200000},"content-version":"vor","delay-in-days":4462,"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":[[1995,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A method of object recognition is proposed based on Dempster\u2010Shafer theory (DS theory), which can treat the ambiguity of image data. A model based object recognition technique based on an aspect imaging method will also be proposed. The aspect imaging method recognizes a similar aspect object by comparing an input image with an aspect image of the model database.<\/jats:p><jats:p>Our proposed method calculates the degree of similarity based on the DS theory instead of Bayes theory, represents an uncertainty factor of similarity as a basic probability of DS theory, and assigns a basic probability of information to be decided. The experimental results show that the proposed method is both more robust and more reliable.<\/jats:p>","DOI":"10.1002\/scj.4690261206","type":"journal-article","created":{"date-parts":[[2007,7,8]],"date-time":"2007-07-08T03:55:54Z","timestamp":1183866954000},"page":"49-57","source":"Crossref","is-referenced-by-count":0,"title":["Model\u2010based object recognition using basic probability assignment"],"prefix":"10.1002","volume":"26","author":[{"given":"Sadaaki","family":"Yamane","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keiji","family":"Aoki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masao","family":"Izumi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kunio","family":"Fukunaga","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","volume-title":"Computer Vision","author":"Ballard D. H.","year":"1982"},{"key":"e_1_2_1_3_2","volume-title":"Machine Vision","author":"Ejiri M.","year":"1990"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/6462.6464"},{"issue":"1","key":"e_1_2_1_5_2","first-page":"30","article-title":"Object Recognition and Geometric Compiler","volume":"4","author":"Ikeuchi K.","year":"1989","journal-title":"Japanese Society for Artificial Intelligence"},{"key":"e_1_2_1_6_2","unstructured":"M.Izumi K.Fukunaga T.FuseandH.Kawakami.Image Segmentation and Object Recognition Based on Aspect Vision. Proc. of the 7th Scandinavian Conf. on Image Analysis pp.291\u2013298(1991)."},{"issue":"9","key":"e_1_2_1_7_2","first-page":"900","article-title":"Dempster\u2010Shafer Theory","volume":"66","author":"Ishizuka M.","year":"1983","journal-title":"Jour. I.E.I.C.E., Japan"},{"key":"e_1_2_1_8_2","volume-title":"Fuzzy Modeling and Its Applications","author":"Tanaka H.","year":"1990"},{"key":"e_1_2_1_9_2","unstructured":"T.MatsuyamaandM.Kurita.Pattern Classification Based on a Dempster\u2010Shafer Probability Model. Proc. of the Meeting on Image Recognition and Understanding (MIRU'92) pp.I\u20109\u2010I\u201016(1992)."},{"key":"e_1_2_1_10_2","unstructured":"T.Shimizu.Binary image recognition system based on fuzzy logic and Dempster\u2010Shafer's theory. I.E.I.C.E. Technical Report PRU89\u20105 (1989)."},{"key":"e_1_2_1_11_2","unstructured":"Toshiba Co. Ltd.Manual of TOSPIX\u2010U pp.378\u2013383(1987)."},{"issue":"9","key":"e_1_2_1_12_2","first-page":"1512","article-title":"Image matching using structures of edge\u2010image graphs","volume":"73","author":"Fukunaga K.","year":"1990","journal-title":"I.E.I.C.E. 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