Camera-based OCR scene text detection issues: A review
1 Department of Computer Science, School of Information and Communication Technology, Federal University of Technology Owerri, Imo State, Nigeria.
2 Department of Mathematics and Computer Science, Clifford University Owerrinta, Abia State, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2021, 12(03), 484–489
Article DOI: 10.30574/wjarr.2021.12.3.0705
Publication history:
Received on 13 November 2021; revised on 21 December 2021; accepted on 23 December 2021
Abstract:
Camera-based scene text detection and recognition is a research area that has attracted countless attention and had made noticeable progress in the area of deep learning technology, computer vision, and pattern recognition. They are highly recommended for capturing text on-scene images (signboards), documents with a multipart and complex background, images on thick books and documents that are highly fragile. This technology encourages real-time processing since handheld cameras are built with very high processing speed and internal memory, are quite easy and flexible to use than the traditional scanner whose usability is limited as they are not portable in size and cannot be used on images captured by cameras. However, characters captured by traditional scanners pose fewer computational difficulties as compared to camera captured images that are associated with divers’ challenges with consequences of high computational complexity and recognition difficulties. This paper, therefore, reviews the various factors that increase the computational difficulties of Camera-Based OCR, and made some recommendations as per the best practices for Camera-Based OCR systems.
Keywords:
Camera-Base; Scene Images; Image Acquisition; OCR; Text Detection; Text Recognition
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0