Multi Orientation Text Detection in Natural Imagery: A Comparative Survey

Multi Orientation Text Detection in Natural Imagery: A Comparative Survey

Deepak Kumar (Lovely Professional University, Phagwara, India) and Ramandeep Singh (Lovely Professional University, Phagwara, India)
Copyright: © 2018 |Pages: 16
DOI: 10.4018/IJCVIP.2018100104

Abstract

Constant advancement and growth in digital technology is swiftly changing the scenario of text detection from hard copy images to natural images. An in-depth study of the previous research work reveals that though a lot of research work has been done on text detection and recognition in natural scene images, but most of the researchers have concluded their survey either on a horizontal or near to horizontal texts. Their survey somewhat speaks about multi-orientation text detection, but the curved text detection in natural images escaped their attention. It has necessitated exploration on the vital aspect of text detection field where detailed study of horizontal, near to horizontal, multi-orientation, and curved text finds a place in a single cover. To achieve this goal, the present study will focus on fundamental understanding, existing challenges, and the proven algorithms for text detection in natural images. The authors discuss the future perspective of recent advances in text detection in natural images with various benchmark datasets and performance metrics.
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3. Applicability And Scope

Ye et al explained the application of text extract comprehensively in Multimedia Retrieval, Visual Input and Assess Industrial Automation three broad categories as illustrated in Figure 1, where the area of applications depicted in the detailed broad categories are put to use. Present application of algorithm being adopted by the researchers are not free from restrictions, limitations and challenges of photometric, geometric and content based challenges. So, there is ample scope of exploration in the sphere of text detection and recognition where all these challenges may not pose any threat of constraint and may be put to use in a free manner on any simple and complex images.

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