A New Approach for Texture based Script Identification At Block Level using Quad Tree Decomposition
Pawan Kumar Singh, Supratim Das, Ram Sarkar, Mita Nasipuri

TL;DR
This paper introduces a novel script identification method using quad-tree decomposition and Gabor wavelet features at block level, achieving high accuracy for multiple Indic scripts.
Contribution
It presents a new approach combining quad-tree decomposition with Gabor wavelet features for script identification at block level, evaluated with multiple classifiers.
Findings
Achieved 96.86% accuracy with MLP classifier
Effective differentiation of 11 Indic scripts
Validated approach with 3-fold cross validation
Abstract
A considerable amount of success has been achieved in developing monolingual OCR systems for Indic scripts. But in a country like India, where multi-script scenario is prevalent, identifying scripts beforehand becomes obligatory. In this paper, we present the significance of Gabor wavelets filters in extracting directional energy and entropy distributions for 11 official handwritten scripts namely, Bangla, Devanagari, Gujarati, Gurumukhi, Kannada, Malayalam, Oriya, Tamil, Telugu, Urdu and Roman. The experimentation is conducted at block level based on a quad-tree decomposition approach and evaluated using six different well-known classifiers. Finally, the best identification accuracy of 96.86% has been achieved by Multi Layer Perceptron (MLP) classifier for 3-fold cross validation at level-2 decomposition. The results serve to establish the efficacy of the present approach to the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHandwritten Text Recognition Techniques · Vehicle License Plate Recognition · Computer Science and Engineering
