An image database of handwritten Bangla words with automatic benchmarking facilities for character segmentation algorithms

作     者：Malakar, Samir Sarkar, Ram Basu, Subhadip Kundu, Mahantapas Nasipuri, Mita 

作者机构：Asutosh Coll Dept Comp Sci Kolkata India Jadavpur Univ Dept Comp Sci & Engn Kolkata India 

出 版 物：《NEURAL COMPUTING & APPLICATIONS》 (神经网络计算与应用)

年 卷 期：2021年第33卷第1期

页      面：449-468页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：PURSE-II, Jadavpur University UPE-II, Jadavpur University DST, Govt. of India [EMR/2016/007213] 

主　　题：Character segmentation Handwritten word Bangla script Image database Word recognition 

摘      要：Recognition of unconstrained handwritten word images is an interesting research problem which gets more challenging when lexicon-free words are considered. Prerequisite for developing a lexicon-free handwritten word recognition technique is the segmentation of a word image into its constituent character set. Therefore, a competent character segmentation technique is required to design a comprehensive word recognition module. However, the literature study reveals that there is no standard word image database with ground truth information. As a result, most character segmentation algorithms found in the literature rely on self-made databases with manual evaluation. To fill the research need, in the present scope of the work, a comprehensive database consisting of handwritten Bangla word images is prepared primarily for evaluating any character segmentation algorithms. Additionally, the present work also provides two types of ground truth images related to segmented character shapes of the word images. Besides, an evaluation tool is developed for assessing the performance of any character segmentation algorithm on the developed benchmark database. The benchmark result, as found here, is 0.9212 (F-score) which outperforms some state-of-the-art methods.