Handwritten Segmentation in Bangla Script: A Review of Offline Techniques

Offline handwritten segmentation in Bangla is an interesting area of research as Segmentation has long been one of the most critical areas of optical character recognition process. Through this operation, an image of a sequence of characters, which may be connected in some cases, is decomposed into sub-images of individual alphabetic symbols. In this paper, segmentation of cursive handwritten script of world’s fourth popular language, Bangla is considered. A stateof-the-art survey about the techniques available in the area of offline handwriting recognition in Bangla scripts will be of a great aid to the researchers. So, a sincere attempt is made in this paper to discuss the advancements reported in this regard during the last few decades. The survey is organized into different sections . A brief introduction is given initially about automatic segmentation of handwriting Bangla scripts. Various Segmentation and classification techniques associated with the offline handwriting recognition of the Bangla scripts are discussed in this survey. A benchmarking database is very important for any pattern recognition related research. The details of the datasets available in Bangla script are also mentioned in the article. A separate section is dedicated to the observations made, future scope, and existing difficulties related to handwriting Segmentation in Bangla scripts. We hope that this survey will serve as a compendium not only for researchers in India, but also for policymakers and practitioners in India. Looking at the recent developments in optical handwritten Recognition of Bangla script, this article will provide a better platform for future research activities.