The INFace (Illumination Normalization techniques for robust Face recognition) toolbox v 2.0 is a collection of Matlab functions and scripts intended to help researchers working in the field of face recognition [COBISS.SI-ID 8737620]. The INFace toolbox v2.0 includes implementations of the following photometric normalization techniques: the single-scale-retinex algorithm, the multi-scale-retinex algorithm, the single-scale self-quotient image, the multi-scale self-quotient image, the homomorphic-filtering-based normalization technique, a wavelet-based normalization technique, a wavelet-denoising-based normalization technique, the isotropic-diffusion-based normalization technique, the anisotropic-diffusion-based normalization technique, the non-local-means-based normalization technique, the adaptive non-local-means-based normalization technique, the DCT-based normalization technique, a normalization technique based on steerable filters, a modified version of the anisotropic-diffusion-based normalization technique, the Gradientfaces approach, the Weberfaces approach, the multi-scale Weberfaces approach, the Tan and Triggs normalization technique and the large and small scale features normalization technique. In addition to the listed techniques there is also a number of histogram manipulation functions included in the toolbox, which can be useful for the task of illumination invariant face recognition. The new (updated) version of the toolbox, which is currently available from its on-line repositories on Matlab Central, the face recognition homepage (http://www.face-rec.org/) and the toolbox’s homepage (http://luks.fe.uni-lj.si/sl/osebje/vitomir/face_tools/INFace/), was downloaded several hundred times since its update in 2011. The toolbox ships with a user manual, which is also listed in the Slovenian bibliographic database COBISS [COBISS.SI-ID 8737876].
F.24 Improvements to existing system-wide, normative and programme solutions, and methods
COBISS.SI-ID: 8737876