Database Development and Recognition of Handwritten Devanagari Legal Amount Words
A dataset containing 26,720 handwritten legal amount words written in Hindi and Marathi languages (Devanagari script) is presented in this paper along with a training-free technique to recognize such handwritten legal amounts present on Indian bank cheques. The recognition of handwritten legal amount words in Hindi and Marathi languages is a challenging because of the similar size and shape of many words in the lexicon. Moreover, many words have same suffixes or prefixes. The recognition technique proposed is a combination of two approaches. The first approach is based on gradient, structural and cavity (GSC) features along with a binary vector matching (BVM) technique. The second approach is based on vertical projection profile (VPP) feature and dynamic time warping (DTW). A number of highly matched words in both the approaches are considered for the recognition step in the combined approach based on a ranking scheme. Syntactical knowledge related to the languages is also used to achieve higher reliability. To the best of our knowledge, this is the first work of its kind in recognizing handwritten legal amounts written in Hindi and Marathi. Researchers interested in the dataset can contact the authors to get through a shared link.
R.Jayadevan S.R.Kolhe P.M.Patil Umapada Pal
Department of IT PICT, Pune, India Department of CS NMU, Jalgaon, India Department of EE VIT, Pune, India CVPR Unit ISI, Kolkata, India
国际会议
北京
英文
304-308
2011-09-01（万方平台首次上网日期，不代表论文的发表时间）