Handwritten Bangla digit recognition using Sparse Representation Classifier

We present a framework for handwritten Bangla digit recognition using Sparse Representation Classifier. The classifier assumes that a test sample can be represented as a linear combination of the train samples from its native class. Hence, a test sample can be represented using a dictionary constructed from the train samples. The most sparse linear representation of the test sample in terms of this dictionary can be efficiently computed through ℓ1-minimization, and can be exploited to classify the test sample. We applied Sparse Representation Classifier on the image zone density, an image domain statistical feature extracted from the character image, to classify the Bangla numerals. This is a novel approach for Bangla Optical Character Recognition, and demonstrates an excellent accuracy of 94% on the off-line handwritten Bangla numeral database CMATERdb 3.1.1. This result is promising, and should be investigated further.

[1]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[2]  E. Ambikairajah,et al.  Speaker verification using sparse representation classification , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[3]  D. Donoho.  For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution , 2006 .

[4]  Khawza I. Ahmed,et al.  Breast cancer classification from ultrasonic images based on sparse representation by exploiting redundancy , 2014, 16th Int'l Conf. Computer and Information Technology.

[5]  Yue Lu,et al.  Handwritten Bangla digit recognition using hierarchical Bayesian network , 2008, 2008 3rd International Conference on Intelligent System and Knowledge Engineering.

[6]  Hiroshi Sako,et al.  Handwritten digit recognition: investigation of normalization and feature extraction techniques , 2004, Pattern Recognit..

[7]  Lambert Schomaker,et al.  A Comparison of Feature and Pixel-Based Methods for Recognizing Handwritten Bangla Digits , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[8]  Trac D. Tran,et al.  Hyperspectral Image Classification Using Dictionary-Based Sparse Representation , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Bidyut B. Chaudhuri.  A Complete Handwritten Numeral Database of Bangla – A Major Indic Script , 2006 .

[10]  Edoardo Amaldi,et al.  On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear Systems , 1998, Theor. Comput. Sci..

[11]  Mahantapas Kundu,et al.  A genetic algorithm based region sampling for selection of local features in handwritten digit recognition application , 2012, Appl. Soft Comput..

[12]  Mallikarjun Hangarge,et al.  Zone Based Features for Handwritten and Printed Mixed Kannada Digits Recognition , 2011 .

[13]  Haibin Ling,et al.  Robust Visual Tracking and Vehicle Classification via Sparse Representation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Ching Y. Suen,et al.  A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters , 2009, Pattern Recognit..