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Text Retrieval from Natural and Scanned Images

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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 and Piyush Daund. Article: Text Retrieval from Natural and Scanned Images. International Journal of Computer Applications 133(8):10-12, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Jayshree Ghorpade-Aher and Sumeet Gajbhar and Amey Sarode and Govardhan Gayake and Piyush Daund},
	title = {Article: Text Retrieval from Natural and Scanned Images},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {8},
	pages = {10-12},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

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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Keywords

Optical Character Recognition (OCR), Pattern Recognition, Automatic Number Plate Recognition (ANPR)