{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T19:36:46Z","timestamp":1760297806975},"reference-count":13,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2007,3,22]],"date-time":"2007-03-22T00:00:00Z","timestamp":1174521600000},"content-version":"vor","delay-in-days":5924,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems &amp; Computers in Japan"],"published-print":{"date-parts":[[1991,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper proposes a gray\u2010level image recognition algorithm based on multiple cell\u2010features for general\u2010purpose model matching using the generalized Hough transform, which removes the instability of conventional edge\u2010segment\u2010based feature description and simplifies its feature matching.<\/jats:p><jats:p>Image features are derived in terms of four basic representations: density; edge direction; edge density; and global edge configuration. These are integrated into a multidimensional feature vector for each \u201ccell,\u201d which is a sampled subregion of the image. This method provides powerful and stable description since it describes contour and area properties as well as local and global features. It also allows the effective use of generalized Hough transform matching.<\/jats:p><jats:p>Multiple cell features are extracted systematically by combining three fundamental operations. These consist of two feature extraction operations, extended convolution and radial traverse probing, and a data compression operation which converts pixel features to cell features by calculating a histogram of extracted features for each cell. Feature dimensionality is decreased efficiently by selecting feature kinds and salient cell positions based on the <jats:italic>F<\/jats:italic>\u2010ratio calculated from training samples. Using the gray\u2010level images of prepaid telephone cards, a recognition experiment with 20 different card images and a positioning experiment with overlapping cards has been carried out.<\/jats:p>","DOI":"10.1002\/scj.4690220509","type":"journal-article","created":{"date-parts":[[2007,7,7]],"date-time":"2007-07-07T20:51:34Z","timestamp":1183841494000},"page":"81-93","source":"Crossref","is-referenced-by-count":1,"title":["Gray\u2010level image recognition based on multiple cell\u2010features"],"prefix":"10.1002","volume":"22","author":[{"given":"Mutsuo","family":"Sano","sequence":"first","affiliation":[]},{"given":"Shinichi","family":"Meguro","sequence":"additional","affiliation":[]},{"given":"Akira","family":"Ishii","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2007,3,22]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1978.1675046"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1983.4767366"},{"key":"e_1_2_1_4_2","article-title":"Grayscale image recognition using multiple cell\u2010features","volume":"85","author":"Sano M.","year":"1985","journal-title":"I.E.C.E., Japan"},{"key":"e_1_2_1_5_2","article-title":"A multiple\u2010feature ex\u2010raction approach to gray\u2010level machine vision system","volume":"47","author":"Meguro S.","year":"1987","journal-title":"IPS Japan"},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(81)90009-1"},{"key":"e_1_2_1_7_2","article-title":"Model\u2010based matching by using feature\u2010integrated cells","volume":"86","author":"Sano M.","year":"1987","journal-title":"I.E.C.E., Japan"},{"key":"e_1_2_1_8_2","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.1980.0020"},{"key":"e_1_2_1_9_2","unstructured":"G.Gerig.Linking image\u2010space and accumulator\u2010space: A new approach for object\u2010recognition. Proc. 1st Int. Conf. Comput. Vis. pp.112\u2013117(1987)."},{"key":"e_1_2_1_10_2","unstructured":"S. D.MaandX.Chen.Hough transform using slope and curvature as local properties. Proc. of 9\u2010ICPR pp.511\u2013513(1988)."},{"key":"e_1_2_1_11_2","first-page":"3","volume-title":"Introduction to Multivariate Analysis II","author":"Kawaguchi M.","year":"1982"},{"issue":"3","key":"e_1_2_1_12_2","first-page":"268","article-title":"Experimental evaluation of the performance of sequential feature selection procedure in statistical pattern classification","volume":"64","author":"Toriwaki J.","year":"1981","journal-title":"I.E.C.E."},{"key":"e_1_2_1_13_2","first-page":"45","volume-title":"Introduction to Multi\u2010variate Analysis I","author":"Kawaguchi M.","year":"1982"},{"key":"e_1_2_1_14_2","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1080\/01621459.1985.10477163","article-title":"Over\u2010smoothed nonparametric density estimates","volume":"80","author":"Terrel G. R.","year":"1981","journal-title":"J. Amer. Statist. Assoc."}],"container-title":["Systems and Computers in Japan"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fscj.4690220509","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/scj.4690220509","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T01:35:17Z","timestamp":1698024917000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/scj.4690220509"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1991,1]]},"references-count":13,"journal-issue":{"issue":"5","published-print":{"date-parts":[[1991,1]]}},"alternative-id":["10.1002\/scj.4690220509"],"URL":"https:\/\/doi.org\/10.1002\/scj.4690220509","archive":["Portico"],"relation":{},"ISSN":["0882-1666","1520-684X"],"issn-type":[{"value":"0882-1666","type":"print"},{"value":"1520-684X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1991,1]]}}}