Objave

@inproceedings{BTAS2009,

title = {Principal Gabor Filters for Face Recognition},

author = {Vitomir Štruc and Rok Gajšek and Nikola Pavešić},

url = {https://lmi.fe.uni-lj.si/en/principalgaborfiltersforfacerecognition/},

doi = {10.1109/BTAS.2009.5339020},

year  = {2009},

date = {2009-09-01},

urldate = {2009-09-01},

booktitle = {Proceedings of the 3rd IEEE International Conference on Biometrics: Theory, Systems and Applications (BTAS'09)},

pages = {1-6},

publisher = {IEEE},

address = {Washington D.C., U.S.A.},

abstract = {Gabor filters have proven themselves to be a powerful tool for facial feature extraction. An abundance of recognition techniques presented in the literature exploits these filters to achieve robust face recognition. However, while exhibiting desirable properties, such as orientational selectivity or spatial locality, Gabor filters have also some shortcomings which crucially affect the characteristics and size of the Gabor representation of a given face pattern. Amongst these shortcomings the fact that the filters are not orthogonal one to another and are, hence, correlated is probably the most important. This makes the information contained in the Gabor face representation redundant and also affects the size of the representation. To overcome this problem we propose in this paper to employ orthonormal linear combinations of the original Gabor filters rather than the filters themselves for deriving the Gabor face representation. The filters, named principal Gabor filters for the fact that they are computed by means of principal component analysis, are assessed in face recognition experiments performed on the XM2VTS and YaleB databases, where encouraging results are achieved.},

keywords = {biometrics, face verification, feature extraction, Gabor features, performance evaluation, principal Gabor filters},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ICSPCS08,

title = {The phase-based Gabor Fisher classifier and its application to face recognition under varying illumination conditions},

author = {Vitomir Štruc and Boštjan Vesnicer and Nikola Pavešić},

doi = {10.1109/ICSPCS.2008.4813663},

isbn = {978-1-4244-4243-0},

year  = {2008},

date = {2008-12-01},

booktitle = {Proceedings of the IEEE International Conference on Signal Processing and Communication Systems (ICSPCS'08)},

pages = {1-6},

publisher = {IEEE},

address = {Gold Coast, Australia},

abstract = {The paper introduces a feature extraction technique for face recognition called the phase-based Gabor Fisher classifier (PBGFC). The PBGFC method constructs an augmented feature vector which encompasses Gabor-phase information derived from a novel representation of face images - the oriented Gabor phase congruency image (OGPCI) - and then applies linear discriminant analysis to the augmented feature vector to reduce its dimensionality. The feasibility of the proposed method was assessed in a series of face verification experiments performed on the XM2VTS database. The experimental results show that the PBGFC method performs better than other popular feature extraction techniques such as principal component analysis (PCA), the Fisherface method or the DCT-mod2 approach, while it ensures similar verification performance as the established Gabor Fisher Classifier (GFC). The results also show that the proposed phase-based Gabor Fisher classifier performs the best among the tested methods when severe illumination changes are introduced to the face images.},

keywords = {biometrics, face verification, feature extraction, Gabor features, performance evaluation, phase congruency features, phase features},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BioID2008,

title = {A palmprint verification system based on phase congruency features},

author = {Vitomir Štruc and Nikola Pavešić},

editor = {Ben Schouten and Niels Christian Juul and Andrzej Drygajlo and Massimo Tistarelli},

url = {https://lmi.fe.uni-lj.si/en/apalmprintverificationsystembasedonphasecongruencyfeatures/},

doi = {10.1007/978-3-540-89991-4_12},

year  = {2008},

date = {2008-01-01},

urldate = {2008-01-01},

booktitle = {Biometrics and Identity Management},

volume = {5372},

pages = {110-119},

publisher = {Springer-Verlag},

address = {Berlin, Heidelberg},

series = {Lecture Notes on Computer Science},

abstract = {The paper presents a fully automatic palmprint verification system which uses 2D phase congruency to extract line features from a palmprint image and subsequently performs linear discriminant analysis on the computed line features to represent them in a more compact manner. The system was trained and tested on a database of 200 people (2000 hand images) and achieved a false acceptance rate (FAR) of 0.26% and a false rejection rate (FRR) of 1.39% in the best performing verification experiment. In a comparison, where in addition to the proposed system, three popular palmprint recognition techniques were tested for their verification accuracy, the proposed system performed the best.},

keywords = {feature extraction, palmprint recognition, palmprint verification, palmprints, performance evaluation},

pubstate = {published},

tppubtype = {inproceedings}

}