TY  - CONF
N2  - This work proposed a geometrical model based on multiple triangular features for the purpose of handling the challenge of scale variations that affect the process of face recognition especially in real time applications where the test images are usually taken in random scales that may not be of the same scale as the probe image. Geometrical approaches have proved to be robust to lighting and illumination variation. Furthermore geometrical methods in general do not hold computational complexity and have the benefit of faster processing time, which make them appropriate for real time applications. Fifteen triangle similarity measurement equations were derived and used to build a class of feature vectors for each subject. Ten images in ten different scales were taken for each subject for a total of fifty samples. Classification results show that the proposed model is promising in handling the challenge of scale variations. © 2013 IEEE.
N1  - cited By 0; Conference of 2013 3rd IEEE International Conference on Signal and Image Processing Applications, IEEE ICSIPA 2013 ; Conference Date: 8 October 2013 Through 10 October 2013; Conference Code:102487
TI  - Scale- invariant face recognition using triangular geometrical model
ID  - scholars3885
SP  - 396
KW  - Face recognition
KW  -  Class; Geometrical modeling; Scale variations; Similarity proportion ratios; Triangular features
KW  -  Geometry
CY  - Melaka
AV  - none
A1  - Ali, A.S.O.
A1  - Asirvadam, V.S.
A1  - Malik, A.S.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894129501&doi=10.1109%2fICSIPA.2013.6708039&partnerID=40&md5=457b1b0ec6171e56194d759c1273475d
EP  - 401
Y1  - 2013///
PB  - IEEE Computer Society
SN  - 9781479902675
ER  -