The Handwritten Bangla Basic character or Numeral recognition is the system by which handwritten Bangla Basic characters or Numerals are scanned into image format and recognize them into machine identifiable format. The process generally includes extraction of features from scanned images, classification of the images by a classifier based on the extracted images. It is worthy to mention here Bangla Basic character consists of 11 vowels and 39 consonants.
Published in Chapter:
Ambiguity Reduction through Optimal Set of Region Selection Using GA and BFO for Handwritten Bangla Character Recognition
Nibaran Das (Jadavpur University, India), Subhadip Basu (Jadavpur University, India), Mahantapas Kundu (Jadavpur University, India), and Mita Nasipuri (Jadavpur University, India)
Copyright: © 2015
|Pages: 29
DOI: 10.4018/978-1-4666-8291-7.ch019
Abstract
To recognize different patterns, identification of local regions where the pattern classes differ significantly is an inherent ability of the human cognitive system. This inherent ability of human beings may be imitated in any pattern recognition system by incorporating the ability of locating the regions that contain the maximum discriminating information among the pattern classes. In this chapter, the concept of Genetic Algorithm (GA) and Bacterial Foraging Optimization (BFO) are discussed to identify those regions having maximum discriminating information. The discussion includes the evaluation of the methods on the sample images of handwritten Bangla digit and Basic character, which is a subset of Bangla character set. Different methods of sub-image or local region creation such as random creation or based on the Center of Gravity (CG) of the foreground pixels are also discussed here. Longest run features, extracted from the generated local regions, are used as local feature in the present chapter. Based on these extracted local features, together with global features, the algorithms are applied to search for the optimal set of local regions. The obtained results are higher than that results obtained without optimization on the same data set.