2011 |
Štruc, Vitomir; Pavešić, Nikola Photometric normalization techniques for illumination invariance Book Section In: Zhang, Yu-Jin (Ed.): Advances in Face Image Analysis: Techniques and Technologies, pp. 279-300, IGI-Global, 2011. Abstract | Links | BibTeX | Tags: biometrics, face recognition, illumination invariance, illumination normalization, photometric normalization @incollection{IGI2011,Face recognition technology has come a long way since its beginnings in the previous century. Due to its countless application possibilities, it has attracted the interest of research groups from universities and companies around the world. Thanks to this enormous research effort, the recognition rates achievable with the state-of-the-art face recognition technology are steadily growing, even though some issues still pose major challenges to the technology. Amongst these challenges, coping with illumination-induced appearance variations is one of the biggest and still not satisfactorily solved. A number of techniques have been proposed in the literature to cope with the impact of illumination ranging from simple image enhancement techniques, such as histogram equalization, to more elaborate methods, such as anisotropic smoothing or the logarithmic total variation model. This chapter presents an overview of the most popular and efficient normalization techniques that try to solve the illumination variation problem at the preprocessing level. It assesses the techniques on the YaleB and XM2VTS databases and explores their strengths and weaknesses from the theoretical and implementation point of view. |
2009 |
Štruc, Vitomir; Pavešić, Nikola Illumination Invariant Face Recognition by Non-Local Smoothing Proceedings Article In: Biometric ID management and multimodal communication, pp. 1-8, Springer-Verlag, Berlin, Heidelberg, 2009. Abstract | Links | BibTeX | Tags: biometrics, face verification, illumination changes, illumination invariance, illumination normalization, pca, preprocessing @inproceedings{BioID_Multi2009,Existing face recognition techniques struggle with their performance when identities have to be determined (recognized) based on image data captured under challenging illumination conditions. To overcome the susceptibility of the existing techniques to illumination variations numerous normalization techniques have been proposed in the literature. These normalization techniques, however, still exhibit some shortcomings and, thus, offer room for improvement. In this paper we identify the most important weaknesses of the commonly adopted illumination normalization techniques and presents two novel approaches which make use of the recently proposed non-local means algorithm. We assess the performance of the proposed techniques on the YaleB face database and report preliminary results. |