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Proceedings Paper

Multi-frame knowledge based text enhancement for mobile phone captured videos
Author(s): Suleyman Ozarslan; P. Erhan Eren
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Paper Abstract

In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

Paper Details

Date Published: 18 February 2014
PDF: 6 pages
Proc. SPIE 9030, Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2014, 90300F (18 February 2014); doi: 10.1117/12.2040606
Show Author Affiliations
Suleyman Ozarslan, Middle East Technical Univ. (Turkey)
P. Erhan Eren, Middle East Technical Univ. (Turkey)


Published in SPIE Proceedings Vol. 9030:
Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2014
Reiner Creutzburg; David Akopian, Editor(s)

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