Offline segmentation and script recognition of Hindi using knowledge based approach and multi layered perceptron neural network. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: Sharma, Neha V; Kavita, ; Aggarwal, Gaurav
• Is Part Of: Journal of statistics & management systems. Volume 20:Issue 4(2017)
• Page Start: 499
• Page End: 506
• Publication Date: 2017-07-04
• Subjects: Hindi Script -- Knowledge Based Approach -- Multi-Layered Perceptron Neural Network; 68T10; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2017.1395170
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: The following paper focusses on a segmentation technique for most widely used language in India i.e. Hindi. Because of variations in writing styles and intricate structures, this field is drawing a lot of attention from researchers. This paper proposes a system which mines and identifies offline Hindi words using MLP Neural Network. Here we are using three layer architecture of neural networks that consists of a layer for Input, Hidden layer and a Resultant layer. Also segmentation is done using Knowledge Based Approach. The success rate after segmentation is 94.87%. Also the overall recognition accuracy is 85.78%.