caa a22 4500 606159126 CHVBK 20210128100623.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00521-015-1824-0 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1824-0 A scalable hybrid decision system (HDS) for Roman word recognition using ANN SVM: study case on Malay word recognition [Elektronische Daten] [Omar Al-Boeridi, S. Syed Ahmad, S. Koh] An off-line handwriting recognition (OFHR) system is a computerized system that is capable of intelligently converting human handwritten data extracted from scanned paper documents into an equivalent text format. This paper studies a proposed OFHR for Malaysian bank cheques written in the Malay language. The proposed system comprised of three components, namely a character recognition system (CRS), a hybrid decision system and lexical word classification system. Two types of feature extraction techniques have been used in the system, namely statistical and geometrical. Experiments show that the statistical feature is reliable, accessible and offers results that are more accurate. The CRS in this system was implemented using two individual classifiers, namely an adaptive multilayer feed-forward back-propagation neural network and support vector machine. The results of this study are very promising and could generalize to the entire Malay lexical dictionary in future work toward scaled-up applications. The Natural Computing Applications Forum, 2015 SVM nationallicence ANN nationallicence Gravity center distance nationallicence Hybrid decision system (HDS) nationallicence Off-line handwriting recognition nationallicence ANN : Adaptive neural network nationallicence CRS : Character recognition system nationallicence H_ANN : High ANN character performance nationallicence H_SVM : High SVM character performance nationallicence HDS : Hybrid decision system nationallicence InC : Ink crossings features nationallicence LWC : Lexical word classification nationallicence MCW : Malay handwritten cheque words nationallicence MCW : Malay cheque word nationallicence MLP : Multilayer perceptron nationallicence MSE : Mean-squared error nationallicence OCR : Optical character recognition nationallicence OFHR : Off-line handwriting recognition nationallicence OHR : Online handwriting recognition nationallicence PS & CG : Pixel density and center gravity distance nationallicence SVM : Support vector machine nationallicence Al-Boeridi Omar School of Electrical and Computer Engineering, RMIT, 3000, Melbourne, VIC, Australia aut Syed Ahmad S. Faculty of Engineering, University Putra Malaysia, 43400, Serdang, Selangor, Malaysia aut Koh S. Center of System and Machine Intelligence, University Tenaga National, 43000, Kajang, Selangor, Malaysia aut Neural Computing and Applications Springer London 26/6(2015-08-01), 1505-1513 0941-0643 26:6<1505 2015 26 521 https://doi.org/10.1007/s00521-015-1824-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1824-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Al-Boeridi Omar School of Electrical and Computer Engineering, RMIT, 3000, Melbourne, VIC, Australia aut NATIONALLICENCE 700 1- Syed Ahmad S. Faculty of Engineering, University Putra Malaysia, 43400, Serdang, Selangor, Malaysia aut NATIONALLICENCE 700 1- Koh S. Center of System and Machine Intelligence, University Tenaga National, 43000, Kajang, Selangor, Malaysia aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/6(2015-08-01), 1505-1513 0941-0643 26:6<1505 2015 26 521