Dipak Kumar Basu

TL;DR: The experimental results show that the csFCM algorithm has superior performance in terms of qualitative and quantitative studies such as, cluster validity functions, segmentation accuracy, tissue segmentsation accuracy and receiver operating characteristic (ROC) curve on the image segmentation results than the k-means, FCM and some other recently proposed FCM-based algorithms.

TL;DR: This paper has described the preparation of a benchmark database for research on off-line Optical Character Recognition (OCR) of document images of handwritten Bangla text and Bangle text mixed with English words, which is the first handwritten database in this area available as an open source document.

TL;DR: A new combination of PCA/MPCA and QTLR features for OCR of handwritten numerals is introduced and it has been observed that MPCA+QTLR feature combination outperforms PCA+QTB feature combination and most other conventional features available in the literature.

TL;DR: A novel hierarchical approach is presented here for optical character recognition (OCR) of handwritten Bangla words that segments a word image on Matra hierarchy, then recognizes the individual word segments and finally identifies the constituent characters of the word image through intelligent combination of recognition decisions of the associated word segments.