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Reseach Article

A Survey on Different Hashing Techniques used for Image Searching

Published on September 2015 by Sapana Prakash Mali, Nitin N. Patil
National Conference on Advances in Communication and Computing
Foundation of Computer Science USA
NCACC2015 - Number 1
September 2015
Authors: Sapana Prakash Mali, Nitin N. Patil
8929933d-1205-431c-8f15-23a1a836c3c2

Sapana Prakash Mali, Nitin N. Patil . A Survey on Different Hashing Techniques used for Image Searching. National Conference on Advances in Communication and Computing. NCACC2015, 1 (September 2015), 32-36.

@article{
author = { Sapana Prakash Mali, Nitin N. Patil },
title = { A Survey on Different Hashing Techniques used for Image Searching },
journal = { National Conference on Advances in Communication and Computing },
issue_date = { September 2015 },
volume = { NCACC2015 },
number = { 1 },
month = { September },
year = { 2015 },
issn = 0975-8887,
pages = { 32-36 },
numpages = 5,
url = { /proceedings/ncacc2015/number1/22327-3039/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Communication and Computing
%A Sapana Prakash Mali
%A Nitin N. Patil
%T A Survey on Different Hashing Techniques used for Image Searching
%J National Conference on Advances in Communication and Computing
%@ 0975-8887
%V NCACC2015
%N 1
%P 32-36
%D 2015
%I International Journal of Computer Applications
Abstract

Image searching, is an active approach to recover the effective results for image searched by the users with the help of queries. Which is used by the current required search engines likes Bing, Google, and Internet Explorer and so on. To improve image searching method there is use of hash code technique. In this paper, various image search techniques using different hashing methods are reviewed. More than a few hashing methods such as state of the art which is used to generate hash codes, then embed and extract features of images in the high-dimensional practice. This scale image search can be executed in real time; this is depends on Hamming distance. This technique contains a weighted Hamming distance and finer-grained ranking. Query adaptive weights consist of semantic concept classes which improves the result of an image search. With the Query adaptive bit weights, images are ranked and calculated by weighted Hamming distance.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Query-adaptive Image Search Scalability Hash Codes Weighted Hamming Distance Query-adaptive Ranking Binary Code Image Search.