Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Kayasth, Manish M.
- Image Segmentation of Handwritten Dates on Bank Cheques
Abstract Views :208 |
PDF Views:2
Authors
Source
National Journal of System and Information Technology, Vol 4, No 1 (2011), Pagination: 117-124Abstract
In this paper Author has described different issues of handwritten date segmentation task briefly along with its techniques. The paper describes a system develop to segments handwritten date information specifically written on bank checks. A system uses a newly adopted segmentation-based strategy. In order to achieve high performance in terms of efficiency and reliability, a knowledge-based module is proposed in order to segments the date. The interaction between the segmentation and recognition stages is properly established by using Segmented-Date generation and evaluation modules. The paper concludes with the current status of the effort made in segmentation of handwritten dates and future enhancement in the same direction.Keywords
OCR, Segmentation, Pattern-based Grammar
References
- Andr´as Kornai, K.M. Mohiuddin et al., An HMM-Based Legal Amount Field OCR System for Checks, IEEE International Conference on Systems, Man and Cybernetics, Vancouver BC, Vol. 3, PP. 2800-2805, 1995.
- C. Y. Suen, Q. Xu et al., Automatic recognition of handwritten data on cheques— fact or fiction? Pattern Recognition Letters, PP. 1287–1295, 1999.
- G. F. Houle, D. B. Aragon et al., A multi-layered corroboration-based check reader, In Proceedings of IAPR Workshop on Document Analysis Systems, USA, PP. 495– 546, October 1996.
- K.S. Sesh Kumar, Anoop M. Namboodiri, et al., Learning Segmentation of Documents with Complex Scripts, Vol. 4338, PP. 749-760, 2006.
- L. Lam, Q. Xu et al., Differentiation between alphabetic and numeric data using ensembles of neural networks, In Proceedings of the 16th International Conference on Pattern Recognition, Canada, Vol. 4, PP. 40–43, August 2002.
- M. Maragoudakis, E. Kavallieratou et al., An Effective Stochastic Estimation of Handwritten Character Segmentation Bounds
- M. Morita, A. El Yacoubi et al., Handwritten month word recognition on Brazilian bank cheques, In Proceedings of the 6th International Conference on Document Analysis and Recognition, USA, PP. 972–976, September 2001.
- R. Fan, L. Lam et al., Processing of date information on cheques, Progress in Handwriting Recognition, World Scientific, Singapore, PP. 473–479, 1997.
- Comprehensive Study on Recognition of Offline Handwritten Gujarati Numerals
Abstract Views :232 |
PDF Views:2
Authors
Affiliations
1 Veer Narmad South Gujarat University, Surat, Gujarat, IN
1 Veer Narmad South Gujarat University, Surat, Gujarat, IN
Source
National Journal of System and Information Technology, Vol 10, No 1 (2017), Pagination: 23-34Abstract
Last few decades, Handwritten Character Recognition (HCR) is one of the most intricate and tricky area in the field of pattern recognition. Research on Optical Character Recognition (OCR) of Gujarati script is very difficult and challenging task due to its complex structural attributes. The most important difficulty with handwritten text is the variability of writing styles, between different writers and between separate examples from the same writer overtime. There is no standard dataset available for handwritten Gujarati characters. Researcher has to develop their own character dataset. Handwritten character/Numeral recognition has received large attention in academics and production fields. This paper will act as guide and update for the readers, working in the field of OCR of Gujarati language. An overview of various statistical and structural features used for recognition based on the various research papers is presented and reviewed.Keywords
Gujarati Numeral Recognition, Off-Line Handwriting Recognition, Feature Extraction, Classification.References
- Snehal S. Patwardhan and R.R. Deshmukh, “Recognition of Offline Handwritten Marathi Characters & Numerals using SVM Classifier”, Asian Journal of Computer Science And Information Technology, Vol. 5, Issue 11,pp. 70-72, Nov. 2015.
- L. Harmon, “Automatic recognition of print and script”, Proc. IEEE, 1972, pp.1165-1176.
- Bhattacharya U. and Chaudhuri B.B., “Handwritten numeral databases of Indian script and multistage recognition of mixed numerals”, IEEE Trans. Pattern and Mach. Intell., Vol. 31, No. 3, pp.444-457, 2009.
- Ramesh Kumar Mohapatra, Tusar Kanti Mishra, Sandeep Panda and Banshidhar Majhi, “OHCS: A Database for Handwritten Atomic Odia Character Recognition”, Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, 2015.
- Desai Apurva A., "Gujarati handwritten numeral optical character reorganization through neural network.", Pattern recognition,Vol 43.7, pp. 2582-2589, 2010.
- Chhaya Patel and Apurva Desai, “Gujarati handwritten character recognition using hybrid method based on binary tree-classifier and k-nearest neighbor", International Journal of Engineering Research Technology (IJERT),vol. 2, issue 6, June-2013, pp. 2278-0181.
- Lipi Shah, Ripal Patel, Shreyal Patel and Jay Maniar, “Handwritten Character Recognition using Radial Histogram" ,International Journal of Research in Advent Technology, 2014 Vol.2, No.4, pp. 2321-9637.
- Desai Apurva A., "Support vector machine for identification of handwritten Gujarati alphabets using hybrid feature space", CSI Transactions on ICT, pp. 1-7, 2015.
- Kamal Moro, Mohammed Fakir and Belaid Bouikhalene, “Handwritten Gujarati Digit Recognition using Sparse Representation Classifier”, International Arab Conference on Information Technology, 2016.
- Archana N. Vyas and Mukesh M. Goswami, “Classification of Handwritten Gujarati Numerals”, International Conference on Advances in Computing, Communications and Informatics (ICACCI),pp. 1231-1237, 2015.
- Kamal S. Galdhariya, Khushali Raval and Shardul Agravat, “A Novel approach to Recognize Handwritten Gujarati Digits”, National Conference on Advances in Computer Science Engineering & Technology, pp. 26-29, May 2017.
- Sharma Ankit, Adhyaru Dipak M. and Zaveri Tanish H., “Chain code feature based recognition of handwritten Gujarati numerals”, International Journal of Advanced Research in Computer Science, Jan-Feb 2017, Vol. 8, Issue 1, pp. 74-77.
- Chhaya C Gohel, Mukesh M Goswami and Vishal K Prajapati, "On-line handwritten Gujarati character Recognition using low level stroke", pp. 130-134, 2015.
- Nafiz Arica and Fatos T. Yarman-Vural,“An Overview of Character Recognition Focused On Off-line Handwriting”, C99-06-C-203, IEEE, 2000.
- Vikas J Dongre and Vijay H Mankar,“A Review of Research on Devnagari Character Recognition”, International Journal of Computer Applications, Vol. 12, No. 2, 2010.
- B. Yu and A. K. Jain,“A Robust and Fast Skew Detection Algorithm for Generic Documents”, Pattern Recognition, 1996.
- Rajiv Kapoor, Deepak Bagai and T. S. Kamal,“Skew angle detection of a cursive handwritten Devnagari script character image”, Journal of Indian Inst. Science, pp. 161-175, May-Aug. 2002.
- K. M. Mohiuddin and J. Mao,“A Comparative Study of Different Classifiers for Handprinted Character Recognition”, Pattern Recognition in Practice IV, pp. 437-448, 1994.
- Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri, D. K. Basu and M. Kundu,“Recognition of Non-Compound Handwritten Devnagari Characters using a Combination of MLP and Minimum Edit Distance”, International Journal of Computer Science and Security (IJCSS), Vol. 4, Issue 1.