Journal ArticleDOI
Handwritten Numeral Databases of Indian Scripts and Multistage Recognition of Mixed Numerals
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TLDR
P pioneering development of two databases for handwritten numerals of two most popular Indian scripts, a multistage cascaded recognition scheme using wavelet based multiresolution representations and multilayer perceptron classifiers and application for the recognition of mixed handwritten numeral recognition of three Indian scripts Devanagari, Bangla and English.Abstract:
This article primarily concerns the problem of isolated handwritten numeral recognition of major Indian scripts. The principal contributions presented here are (a) pioneering development of two databases for handwritten numerals of two most popular Indian scripts, (b) a multistage cascaded recognition scheme using wavelet based multiresolution representations and multilayer perceptron classifiers and (c) application of (b) for the recognition of mixed handwritten numerals of three Indian scripts Devanagari, Bangla and English. The present databases include respectively 22,556 and 23,392 handwritten isolated numeral samples of Devanagari and Bangla collected from real-life situations and these can be made available free of cost to researchers of other academic Institutions. In the proposed scheme, a numeral is subjected to three multilayer perceptron classifiers corresponding to three coarse-to-fine resolution levels in a cascaded manner. If rejection occurred even at the highest resolution, another multilayer perceptron is used as the final attempt to recognize the input numeral by combining the outputs of three classifiers of the previous stages. This scheme has been extended to the situation when the script of a document is not known a priori or the numerals written on a document belong to different scripts. Handwritten numerals in mixed scripts are frequently found in Indian postal mails and table-form documents.read more
Citations
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Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms
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Feature selection based classifier combination approach for handwritten Devanagari numeral recognition
TL;DR: The main contribution of the proposed method for the recognition of handwritten Hindi numerals is that, the method gives quite efficient results utilizing only 10% patterns of the available dataset.
Proceedings ArticleDOI
Off-line Recognition of Hand-Written Bengali Numerals Using Morphological Features
Pulak Purkait,Bhabatosh Chanda +1 more
TL;DR: This paper uses different multi-layer perceptron (MLP) classifiers to train this feature spaces and then fuse those classifiers using modified ‘Naive’-Bayes combination to increase accuracy of recognition result.
Journal ArticleDOI
Odia character recognition: a directional review
TL;DR: A new handwritten alphanumeric character database for Odia is created and reported in this paper in order to address the paucity of benchmark Odia database.
Book ChapterDOI
Offline Handwritten Malayalam Word Recognition Using a Deep Architecture
TL;DR: A pioneering development of a database for offline handwritten word samples of Malayalam script and its benchmark recognition results based on a transfer learning strategy which involves a deep convolutional neural network (CNN) architecture for feature extraction and a support vector machine (SVM) for classification are presented.
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