Multi-frame knowledge based text enhancement for mobile phone captured videos

2014-02-05
Ozarslan, Suleyman
Eren, Pekin Erhan
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%.

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Citation Formats
S. Ozarslan and P. E. Eren, “Multi-frame knowledge based text enhancement for mobile phone captured videos,” 2014, vol. 9030, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31790.