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Reseach Article

Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels

by H. B. Kekre, Sudeep Thepade, Sanchit Khandelwal, Adnan Azmi, Karan Dhamejani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 20
Year of Publication: 2012
Authors: H. B. Kekre, Sudeep Thepade, Sanchit Khandelwal, Adnan Azmi, Karan Dhamejani
10.5120/7923-1259

H. B. Kekre, Sudeep Thepade, Sanchit Khandelwal, Adnan Azmi, Karan Dhamejani . Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels. International Journal of Computer Applications. 50, 20 ( July 2012), 39-45. DOI=10.5120/7923-1259

@article{ 10.5120/7923-1259,
author = { H. B. Kekre, Sudeep Thepade, Sanchit Khandelwal, Adnan Azmi, Karan Dhamejani },
title = { Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 20 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 39-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number20/7923-1259/ },
doi = { 10.5120/7923-1259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:48:51.849869+05:30
%A H. B. Kekre
%A Sudeep Thepade
%A Sanchit Khandelwal
%A Adnan Azmi
%A Karan Dhamejani
%T Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 20
%P 39-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper presents a performance analysis of Multilevel Block Truncation Coding based Face Recognition on BTC-Intermediate- 4 and BTC-Intermediate-9 techniques. In [1], Multilevel Block Truncation Coding was applied on the RGB color space up to four levels for face recognition. Similarly in this paper, Multilevel Block Truncation Coding is implemented on BTC-Intermediate-4 and BTC-Intermediate-9. For experimental analysis, two face databases are used. First one is "Face Database", developed by Dr. Libor Spacek which has 1000 face images and the second one is "Our Own Database" which has 1600 face images. The experimental results showed that Block Truncation Level 4 (BTC-Level 4) gave the best result when applied on whole image as compared to BTC-Intermediate-4 and BTC-Intermediate-9 techniques.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Face recognition Block Truncation Coding RGB Multilevel BTC