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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Naganjaneyulu, G. V. S. S. K. R. Narasimhadhan, A. V. Venkatesh, K. |
| Copyright Year | 2014 |
| Description | Author affiliation: Department of Electronics and Communications Engineering, National Institute of Technology, Surathkal, India (Narasimhadhan, A. V.) || Department of Electronics and Communications Engineering, Rajiv Gandhi University of Knowledge Technologies, Krishna, India (Naganjaneyulu, G V S S K R; Venkatesh, K) |
| Abstract | The performance of optical character recognition (OCR) algorithm is poor on low resolution scanned text images. The conventional low pass filters in L2 space can slightly improve the performance. The method of enhancement of poor resolution text images using a low pass signal filtering algorithm in the weighted Sobolev space results in high pass correction similar to un sharp masking. This can further improve the performance of OCR on low resolution text images. In this paper, the performance of a typical OCR system on low resolution scanned text images, is studied without using any preprocessing step, with low pass filtering in L2 space, and compared with low pass filtering in weighted Sobolev space as pre processing steps. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 672503 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479940769 |
| ISSN | 21593450 |
| e-ISBN | 9781479940752 |
| DOI | 10.1109/TENCON.2014.7022357 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-10-22 |
| Publisher Place | Thailand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Optical character recognition software Image resolution Accuracy Signal resolution Filtering theory Character recognition Image recognition Optical Character Recognition Gaussian Filter Weighted Sobolev Space Enhancement |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Computer Science Applications |
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