A Study on Significance of Color in Face Recognition using Several Eigenface Algorithms

Distributed Computing and Artificial Intelligence, 13th International Conference

et al. 2016

Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR color space on face recognition for surveillance applications is investigated and compared with the performance of the gray scale. In addition, the performance of fusing two or more color channels is also compared with that of the gray scale. Three cases with different number of training images per persons were used as a test bed. It was found out that, the gray scale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the gray scale when three images of the same class from the same database are used for training. The CBxCR channel gave the best performance for the individual color channels followed by CB, CB-CR, CB/CR and CR respectively. It was also found that, in general, increasing the number of fused channels in-creases the performance of the system.

Section: Introductionmentioning

confidence: 99%

A Comparison of the YCBCR Color Space with Gray Scale for Face Recognition for Surveillance Applications

Dargham

Chekima

Distributed Computing and Artificial Intelligence, 13th International Conference

et al. 2016

“…There are several reports that have reported the effect of colour spaces in biometric fields. Karimi and Devroye (2007) reported that using colour images with PCA-based face recognition system improves the recognition accuracy. Chaves-González et al (2010) investigated the effect of colour spaces for face detection application using RGB, CMY, YUV, YIQ, YP B P R , YC B C R , YC G C R , YD B D R , HSV-or HSI-and CIE-XYZ.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of the YCBCR Color Space with Gray Scale for Face Recognition for Surveillance Applications

Dargham

Chekima

et al. 2018

ADCAIJ

Principal Component Analysis; YCBCR colour space; face recognition; surveillance applicationsFace recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR colour space on face recognition for surveillance applications is investigated and compared with the performance of the gray scale. In addition, the performance of fusing two or more colour channels is also compared with that of the gray scale. Three cases with different number of training images per persons were used as a test bed. It was found out that, the gray scale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the gray scale when three images of the same class from the same database are used for training. Regardless of the cases used, the CBxCR channel always gave the best performance for the individual colour channels. It was found that, in general, increasing the number of fused channels increases the performance of the system. It was also found that the gray scale channel is the better choice for face recognition since it contain better quality edges and visual features which are essential for face recognition.

“…There are several reports that have reported the effect of color spaces in biometric fields. Karimi and Devroye (2007) reported that using color images with PCA-based face recognition system improves the recognition accuracy. Chaves-González et al (2010) investigated the effect of color spaces for face detection application using RGB, CMY, YUV, YIQ, YP B P R , YC B C R , YC G C R , YD B D R , HSV-or HSI-and CIE-XYZ.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of the YCBCR Color Space with Gray Scale for Face Recognition for Surveillance Applications

2017

ADCAIJ

Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR color space on face recognition for surveillance applications is investigated and compared with the performance of the gray scale. In addition, the performance of fusing two or more color channels is also compared with that of the gray scale. Three cases with different number of training images per persons were used as a test bed. It was found out that, the gray scale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the gray scale when three images of the same class from the same database are used for training. Regardless of the cases used, the CBxCR channel always gave the best performance for the individual color channels. It was found that, in general, increasing the number of fused channels increases the performance of the system. It was also found that the gray scale channel is the better choice for face recognition since it contain better quality edges and visual features which are essential for face recognition.