TY - CONF AV - none TI - Face recognition technique using Gabor wavelets and Singular Value Decomposition (SVD) ID - scholars4340 SP - 455 KW - Gabor filters; Singular value decomposition; Vectors KW - Computational time; Face recognition systems; Face recognition technique; Face Verification; Gabor wavelets; Prominent features; Rejection rates; Singular vectors KW - Face recognition N2 - Gabor wavelets (also known as Gabor filters) and Singular Value Decomposition (SVD) have been exploited extensively in the area of face recognition. In this paper, a face recognition system is developed combining features extracted using both Gabor wavelets and SVD. For Gabor wavelets, the extracted feature vectors are selected from only 12 out of 40 Gabor wavelets. The outputs from the 12 filters are selected because it provides relatively more prominent features than the other. This offers the advantage of reducing computational time. As for SVD, only the first five singular values are selected and its associated right singular vectors are used as the feature vectors. The five singular vectors are the one that carry the maximal energy of the image. The combination of Gabor wavelets and SVD offers the advantage of increasing the reliability of the face recognition system. In the face verification stage, the similarity level between facial images is determined by computing the distance between the resulting facial feature vectors obtained from Gabor wavelets and SVD, respectively. The experimental result tested using JAFFE database indicates an average correct acceptance rate of 75.2 and correct rejection rate of 100. The results show that the combined methods provide a reliable face recognition system. © 2014 IEEE. N1 - cited By 3; Conference of 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014 ; Conference Date: 28 November 2014 Through 30 November 2014; Conference Code:111756 PB - Institute of Electrical and Electronics Engineers Inc. SN - 9781479956869 Y1 - 2014/// EP - 459 A1 - Li, L.S. A1 - Yahya, N. UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686218&doi=10.1109%2fICCSCE.2014.7072762&partnerID=40&md5=9473a6b2ce03cf84aa1695af5f94b091 ER -