Title: Detecting Gurmukhi and Hindi text object present in images

Authors: Rahul Malik

Addresses: Department of Computer Science and Engineering, Lovely Professional University, Punjab, India

Abstract: This paper resolves the trouble detecting Gurmukhi and Hindi text objects present in images. Therefore, we propose a new region-based bottom-up method to extract text from images, where we first identify elementary substructures using connected components and edges and then merge them successively. As each character counter has high contrast as compared to its neighbours, all character pixels and several non-character pixels which exhibit excessive neighbourhood. Although a lot of noise is removed by this step a second pass filter is applied based on stroke width. The stroke width of Hindi and Gurmukhi characters are approximately uniform. The candidates with similar properties are aggregated into chains, according to the observation that the figures of a book. For performance evaluation, we created our own dataset containing 60 images of varied size, resolution and type. The performance is evaluated on this dataset containing caption, document, and scene text images using different performance metrics.

Keywords: Gurmukhi; precision; recall.

DOI: 10.1504/IJCSYSE.2020.111220

International Journal of Computational Systems Engineering, 2020 Vol.6 No.2, pp.100 - 108

Received: 26 Mar 2020
Accepted: 20 Aug 2020
Published online: 13 Nov 2020 *

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