Title :
Energy efficient face recognition using row, column feature vectors of Slant Transform and performance comparison with PCA
Author :
Kekre, H.B. ; Shah, Kamal
Author_Institution :
MPSTME, SVKM´´s NMIMS Univ., Mumbai, India
Abstract :
In this paper we propose fast face recognition system based on the 1-D Discrete Slant Transform (ST) row feature vector-RV and column feature vector-CV. This scheme is less complicated and needs less time as compared to ST of full image. It is observed that in this method for 95% image energy the coefficient requirement reduces drastically compared to PCA and full ST which improves the recognition efficiency of algorithm. We have used standard ORL database and results obtained are accurate. The algorithm is also tested for locally created database of male and female faces which gives accuracy around 90%.
Keywords :
discrete transforms; face recognition; PCA performance comparision; ST full image; column feature vector CV; discrete slant transform; energy efficient face recognition; fast face recognition system; feature vector RV; locally created database; recognition efficiency algorithm; row feature vectors; standard ORL database; Biometrics; Compaction; Energy efficiency; Face recognition; Image databases; Image recognition; Principal component analysis; Spatial databases; Testing; Wavelet transforms; Column Feature Vector; Eigenfaces; Energy compaction; Face recognition; PCA; Row feature vector; Slant Transform (ST);
Conference_Titel :
Industrial Electronics & Applications, 2009. ISIEA 2009. IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-4681-0
Electronic_ISBN :
978-1-4244-4683-4
DOI :
10.1109/ISIEA.2009.5356487