A new large urdu database for off-line handwriting recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5716 LNCS, Issue , 2009, Pages 538-546

  Sagheer, Malik Waqas ^a   He, Chun Lei ^a   Nobile, Nicola ^a   Suen, Ching Y ^a  

^a Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

Handwriting Segmentation; Off line Handwriting Recognition; Urdu Digit Recognition; Urdu OCR

Indexed keywords

DIGIT RECOGNITION; GRADIENT FEATURE; GRAY LEVELS; HANDWRITING SEGMENTATION; IMAGE PREPROCESSING; MACHINE INTELLIGENCE; NUMERAL STRINGS; OFFLINE HANDWRITING RECOGNITION; SPECIAL SYMBOLS; TRUE COLORS;

DATABASE SYSTEMS; ERROR ANALYSIS; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE SEGMENTATION;

CHARACTER RECOGNITION;

EID: 76249103315     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04146-4_58     Document Type: Conference Paper

References (6)

1. Anwar, W., Wang, X., Wang. X.-L.: A survey of automatic Urdu language processing. In: Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, pp. 13-16 (2006)
2. Dehghan, M., Faez, K., Ahmadi, M., Shridhar, M.: Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM. Pattern Recognition 34(5), 1057-1065 (2001)
3. Liu, C.-L., Nakashima, K., Sako, H., Fujisawa, H.: Handwritten digit recognition: Investigation of normalization and feature extraction techniques. Pattern Recognition 37(2), 265-279 (2004)
4. Liu, C.-L., Suen, C.Y.: A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters. In: Proceedings of 11th International Conference on Frontiers in Handwriting Recognition (ICFHR), Montreal, Canada, pp. 278-283 (2008)
5. Otsu, N.: A threshold selection method from gray-level histogram. IEEE Trans. System Man Cybernet. 9, 1569-1576 (1979)
6. Shi, M., Fujisawa, Y., Wakabayashi, T., Kimura, F.: Handwritten numeral recognition using gradient and curvature of gray scale image. Pattern Recognition 35(10), 2051-2059 (2002)