Abstract
The paper presents a performance analysis of Multilevel Block Truncation Coding based Face Recognition on BTCIntermediate4 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 BTCIntermediate-4 and BTC-Intermediate-9 techniques.
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