UGC Approved Journal no 63975(19)

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Published in:

Volume 5 Issue 5
May-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1805939


Registration ID:
304051

Page Number

1170-1174

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Title

Content Based Document Image Retrieval: A Review

Abstract

Information and Communication Technology (ICT) has influenced the people by facilitating large storage, instantaneous transmission, efficient processing and enhanced retrieval of data. With its economic feasibility along with the extraordinary development of the technological tools, including the availability of high end image acquisition and capturing devices such as digital cameras & scanners, the possibility of maintaining large collections of digital images has realized and is growing constantly. Maintaining the large repositories of document images has however created an incredible need to access and manipulate document images using effective permissible ways. Proficient image searching and retrieval tools are demanded by users from various domains that include medicine, remote sensing, entertainment, architecture and many more in order to bring efficiency in their respective extents. In this direction, many general purpose image retrieval systems have been developed particularly in the form of text and content based frameworks. In text based systems, the document images are manually annotated by text descriptors which are then used by a conventional database management system to perform the identification and retrieval. This approach however has two significant disadvantages; first a reasonable level of human labor & skill is required for manual annotation; second is the annotation inaccuracy due to the subjectivity of human perception. In content based image retrieval systems, images are indexed by their visual content and the fundamental idea requires the user to provide a description of some of the prominent visual features of the image such as color, texture and shape. The designed system can search the archive subsequently and return the images that best match the description. Many researchers focused on content based image indexing and retrieval using only color as visual feature. There are several projects in this field such as Query By Image Content (QBIC), Visual Information Retrieval (VIR), Multimedia Analysis & Retrieval System (MARS) and many alike. The fundamental consideration in the design & development of a content based image retrieval system is to extract the image features that best represent the image contents in a database.

Key Words

Content Based Image Retrieval, Document Image, Image Indexing

Cite This Article

"Content Based Document Image Retrieval: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.1170-1174, May-2018, Available :http://www.jetir.org/papers/JETIR1805939.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Content Based Document Image Retrieval: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp1170-1174, May-2018, Available at : http://www.jetir.org/papers/JETIR1805939.pdf

Publication Details

Published Paper ID: JETIR1805939
Registration ID: 304051
Published In: Volume 5 | Issue 5 | Year May-2018
DOI (Digital Object Identifier):
Page No: 1170-1174
Country: Pulwama, Jammu & Kashmir, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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