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- Publisher
- Inderscience Publishers
- Copyright
- Copyright © Inderscience Enterprises Ltd. All rights reserved
- ISSN
- 1748-0698
- eISSN
- 1748-0701
- DOI
- 10.1504/IJSISE.2009.033759
- Publisher site
- See Article on Publisher Site
Abstract
This paper presents a unified approach for the extraction of text from heterogeneous and hybrid textual images (both scene text and caption text in an image) and document images with variations in illumination, transformation/perspective projection, font size and radially changing/angular text. The strength of this technique lies in producing small number of features at less running time for the extraction of text from heterogeneous images in various priority levels. Proposed feature selection algorithm is evaluated with three common Machine-Learning (ML) algorithms and effectiveness is shown by comparing with three feature selection methods. The qualitative analysis proves the encouraging performance of the proposed text extraction system in comparison with the edge-, Connected-Component- (CC) and texture-based text extraction algorithm.
Journal
International Journal of Signal and Imaging Systems Engineering – Inderscience Publishers
Published: Jan 1, 2009