tailieunhanh - Báo cáo hóa học: " Research Article Arabic Handwritten Word Recognition Using HMMs with Explicit State Duration"

Tham khảo luận văn - đề án 'báo cáo hóa học: " research article arabic handwritten word recognition using hmms with explicit state duration"', luận văn - báo cáo phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 247354 13 pages doi 2008 247354 Research Article Arabic Handwritten Word Recognition Using HMMs with Explicit State Duration A. Benouareth 1 A. Ennaji 2 and M. Sellami1 1 Laboratoire de Recherche en Informatique Departement d Informatique Universite Badji Mokhtar Annaba BP 12- 23000 SidiAmar Algeria 2 Laboratoire LITIS FRE 2645 Universite de Rouen 76800 Madrillet France Correspondence should be addressed to A. Benouareth benouareth@ Received 09 March 2007 Revised 20 June 2007 Accepted 28 October 2007 Recommended by . Kuo We describe an offline unconstrained Arabic handwritten word recognition system based on segmentation-free approach and discrete hidden Markov models HMMs with explicit state duration. Character durations play a significant part in the recognition of cursive handwriting. The duration information is still mostly disregarded in HMM-based automatic cursive handwriting recognizers due to the fact that HMMs are deficient in modeling character durations properly. We will show experimentally that explicit state duration modeling in the HMM framework can significantly improve the discriminating capacity of the HMMs to deal with very difficult pattern recognition tasks such as unconstrained Arabic handwriting recognition. In order to carry out the letter and word model training and recognition more efficiently we propose a new version of the Viterbi algorithm taking into account explicit state duration modeling. Three distributions Gamma Gauss and Poisson for the explicit state duration modeling have been used and a comparison between them has been reported. To perform word recognition the described system uses an original sliding window approach based on vertical projection histogram analysis of the word and extracts a new pertinent set of statistical and structural features from the word image. Several experiments have been .

TÀI LIỆU LIÊN QUAN