{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,18]],"date-time":"2025-05-18T15:05:17Z","timestamp":1747580717793},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[1993,4]]},"abstract":"<jats:p> This paper proposes a probabilistic approach to recognize handwritten Chinese characters. According to the stroke writing sequence, strokes and interleaved stroke relations are built manually as a 1-D string, called an on-line model, to describe a Chinese character. In an input character, strokes are first extracted by a tree searching method. The recognition problem is then formulated as an optimization matching problem in a multistage directed graph, where the number of stages is the length of the modelled stroke sequence. Nodes in a stage represent extracted strokes that have the same stroke type as defined in the on-line model and the link between two neighboring nodes corresponds to the relationship between the two extracted strokes. The probability that the extracted stroke belongs to the predefined stroke type is calculated from the stroke line segments, and the transition probability between two extracted strokes is the degree of satisfaction of the relationship defined in the on-line model. The Viterbi algorithm, which can handle stroke insertion, deletion, splitting, and merging, is applied to recover the sequence of strokes consisting of the unknown character. The similarity is defined to be the product of stroke probabilities and stroke transition probabilities in the stroke sequence. The unknown character is matched with all modelled characters and is recognized as the one with the highest similarity. Experiments with 540 characters uniformly selected from the database CCL\/HCCR1 (250 variations\/class) are conducted, and the recognition rate is about 92.8%, which proves the feasibility of the proposed recognition system. <\/jats:p>","DOI":"10.1142\/s0218001493000170","type":"journal-article","created":{"date-parts":[[2004,11,22]],"date-time":"2004-11-22T22:29:30Z","timestamp":1101162570000},"page":"329-352","source":"Crossref","is-referenced-by-count":10,"title":["A PROBABILISTIC STROKE-BASED VITERBI ALGORITHM FOR HANDWRITTEN CHINESE CHARACTERS RECOGNITION"],"prefix":"10.1142","volume":"07","author":[{"given":"CHEN-CHUNG","family":"HSIEH","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Chiao Tung University, Hsinchu, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HSI-JIAN","family":"LEE","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Chiao Tung University, Hsinchu, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001493000170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T22:15:21Z","timestamp":1565129721000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001493000170"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1993,4]]},"references-count":0,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1993,4]]}},"alternative-id":["10.1142\/S0218001493000170"],"URL":"https:\/\/doi.org\/10.1142\/s0218001493000170","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[1993,4]]}}}