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

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International Journal of Computer Applications
© 2012 by IJCA Journal
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 and Karan Dhamejani. Article: Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels. International Journal of Computer Applications 50(20):39-45, July 2012. Full text available. BibTeX

@article{key:article,
	author = {H. B. Kekre and Sudeep Thepade and Sanchit Khandelwal and Adnan Azmi and Karan Dhamejani},
	title = {Article: Implementation of Multilevel Block Truncation based Face Recognition on Intermediate-4 and Intermediate-9 levels},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {50},
	number = {20},
	pages = {39-45},
	month = {July},
	note = {Full text available}
}

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.

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