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Reseach Article

Heterogeneous Face Matching: NIR Images to VIS Images

Published on March 2017 by Sandhya R.waddhavane, S.m.kamalapur
Emerging Trends in Computing
Foundation of Computer Science USA
ETC2016 - Number 3
March 2017
Authors: Sandhya R.waddhavane, S.m.kamalapur

Sandhya R.waddhavane, S.m.kamalapur . Heterogeneous Face Matching: NIR Images to VIS Images. Emerging Trends in Computing. ETC2016, 3 (March 2017), 5-9.

author = { Sandhya R.waddhavane, S.m.kamalapur },
title = { Heterogeneous Face Matching: NIR Images to VIS Images },
journal = { Emerging Trends in Computing },
issue_date = { March 2017 },
volume = { ETC2016 },
number = { 3 },
month = { March },
year = { 2017 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/etc2016/number3/27314-6268/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 Emerging Trends in Computing
%A Sandhya R.waddhavane
%A S.m.kamalapur
%T Heterogeneous Face Matching: NIR Images to VIS Images
%J Emerging Trends in Computing
%@ 0975-8887
%V ETC2016
%N 3
%P 5-9
%D 2017
%I International Journal of Computer Applications

Heterogeneous (cross spectral) face matching is very important in many of the security applications, especially at night time face recognition where query images are near infrared face images and gallery images are generally visible light images. At night time environment near infrared cameras are used for imaging and images can be captured at various distances as object is not at fix position. As distance increases the quality of face image get degrade and it becomes difficult to match the query near infrared face image with the gallery images. The aim of proposed work is to implement an efficient face matching technique that resolves the problem of cross distance together with cross spectral face matching. Learning based image restoration is an approach to deal with this problem. In this the face images at long distances are restored first and then restored face images are matched with VIS (database) images. The proposed work improves the face matching performance by normalizing near infrared and visible light face images using Difference of Gaussian filter and extracted HOG features for heterogeneous face matching.

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Index Terms

Computer Science
Information Sciences


Acquisition System Cross Spectral Cross Distance Heterogeneous Face Image Restoration Near Infrared (nir) Face Image Visible Light (vis) Face Image