Active contour based optical character recognition for automated scene understanding

Olszewska, Joanna Isabelle (2015) Active contour based optical character recognition for automated scene understanding. Neurocomputing, 161. pp. 65-71. doi:10.1016/j.neucom.2014.12.089

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Abstract

In this paper, we present a new optical character recognition (OCR) approach which allows real-time, automatic extraction and recognition of digits in images and videos. Our method relies on active contours in order to robustly extract optical characters from real-world visual scenes. The detected character recognition is based on template matching. Our developed system has shown excellent results when applied to the automated identification of team players' numbers in sport datasets and has outperformed state-of-the-art methods.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Pattern recognition; Information fusion; Fast segmentation; Scene-text localization and extraction; Active contours; Snake evolution
Related URLs:	Publisher
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Susan Turner
Date Deposited:	22 Jan 2016 16:00
Last Modified:	31 Aug 2023 08:01
URI:	https://eprints.glos.ac.uk/id/eprint/3021

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