Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. / Forczmański, Paweł; Kukharev, Georgy; Shchegoleva, Nadezdha.
Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings. PART 1. ред. 2013. стр. 602-611 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 8156 LNCS, № PART 1).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations
AU - Forczmański, Paweł
AU - Kukharev, Georgy
AU - Shchegoleva, Nadezdha
PY - 2013/10/3
Y1 - 2013/10/3
N2 - The paper addresses the problem of face recognition for images registered in variable lighting, which is common for real-world conditions. Presented algorithm is based on orthogonal transformation preceded by simple transformations comprising of equalization of brightness gradients, removal of spatial low frequency spectral components and fusion of spectral features depending on average pixels intensity. Two types of transformations: 2DDCT (two-dimensional Discrete Cosine Transform) and 2DKLT (two-dimensional Karhunen-Loeve Transform) were investigated in order to find the most optimal algorithm setup. The results of experiments conducted on Yale B and Yale B+ datasets show that a quite simple algorithm is capable of successful recognition without high computing power demand, as opposite to several more sophisticated methods presented recently.
AB - The paper addresses the problem of face recognition for images registered in variable lighting, which is common for real-world conditions. Presented algorithm is based on orthogonal transformation preceded by simple transformations comprising of equalization of brightness gradients, removal of spatial low frequency spectral components and fusion of spectral features depending on average pixels intensity. Two types of transformations: 2DDCT (two-dimensional Discrete Cosine Transform) and 2DKLT (two-dimensional Karhunen-Loeve Transform) were investigated in order to find the most optimal algorithm setup. The results of experiments conducted on Yale B and Yale B+ datasets show that a quite simple algorithm is capable of successful recognition without high computing power demand, as opposite to several more sophisticated methods presented recently.
KW - DCT
KW - dimensionality reduction
KW - face recognition
KW - illumination compensation
KW - PCA
UR - http://www.scopus.com/inward/record.url?scp=84884705275&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-41181-6_61
DO - 10.1007/978-3-642-41181-6_61
M3 - Conference contribution
AN - SCOPUS:84884705275
SN - 9783642411809
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 602
EP - 611
BT - Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings
T2 - 17th International Conference on Image Analysis and Processing, ICIAP 2013
Y2 - 9 September 2013 through 13 September 2013
ER -
ID: 49225328