论文信息 - Handwritten Recognition using Slope and Curvature Functions

Handwritten Recognition using Slope and Curvature Functions

Letter recognition and handwritten processing is one of the major and open problems in Artificial Intelligent (AI) domain. This study introduces a method based on statistical and geometrical techniques to recognize handwritten digits and letters. These techniques use the fuzzy logic to create the vector curves. Inputs are online digits or letters and outputs are two arrays of slope and curvature values. The slope and curvature values of training data are stored in a database and used in comparison phase. The test results show that 96.98% of inputs are correctly recognized. General Terms Pattern recognition, Fuzzy logic, Persian digits & letters

Soheila Karbasi | Mehdi Yaghoubi | Soheila Karbasi | M. Yaghoubi

[1] Ehsanollah Kabir,et al. Introducing a very large dataset of handwritten Farsi digits and a study on their varieties , 2007, Pattern Recognit. Lett..

[2] H. Ishibuchi,et al. Distributed representation of fuzzy rules and its application to pattern classification , 1992 .

[3] Cheng-Lin Liu,et al. Handwritten digit recognition: benchmarking of state-of-the-art techniques , 2003, Pattern Recognit..

[4] Meng Shi,et al. Handwritten numeral recognition using gradient and curvature of gray scale image , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).