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Text Retrieval from Natural and Scanned Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 133 - Number 8 |
| Year of Publication: 2016 |
| Authors: Jayshree Ghorpade-Aher, Sumeet Gajbhar, Amey Sarode, Govardhan Gayake, Piyush Daund |
10.5120/ijca2016907840
|
Jayshree Ghorpade-Aher, Sumeet Gajbhar, Amey Sarode, Govardhan Gayake, Piyush Daund . Text Retrieval from Natural and Scanned Images. International Journal of Computer Applications. 133, 8 ( January 2016), 10-12. DOI=10.5120/ijca2016907840
Abstract
Digital documents are easy to handle, share and store than hard copy of documents. These made people to prefer digital document over hard copy of documents. Digital documents are nothing but scanned images of a document or natural images of notice boards, traffic signs. Text detection is an important process required to extract text from images. Text from images can be extracted using Optical Character Recognition (OCR). OCR works in three phases as pre-processing, segmentation, character recognition. Pre-processing is the first phase which uses different techniques for making text easy to extract from images. In segmentation phase, each character is isolated. Then this will be given as input to OCR recognition phase which will compare it with training data-set and will recognize character. In this survey paper, different techniques for OCR are discussed.
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