Inspired by Fechner's law, we propose a Fechner multiscale local descriptor (FMLD) for
feature extraction and face recognition. Fechner's law is a well-known law in psychology …

Literature suggests that by fusing multiple features there is immense improvement in the
recognition rates as compared to the recognition rates of single descriptor. This motivate …

Face recognition is among the few biometric recognition systems that produces a high level
of accuracy and requires simple, straightforward implementation [1]. People can recognize …

Human perception of visual stimulus and its physical characteristics have a nonlinear-
logarithmic relation as stated in Fechner's law, which is a psychophysical law of perception …

Human perception of a signal depends on the ratio of the change of stimulus to the stimulus
itself while the change of stimulus to the stimulus itself is usually ignored in hand-crafted …

Most of LBP based descriptors develop their feature size by considering the uniform
coordination among neighbors and center pixel. Additionally, most of them possesses noisy …

This paper presents a method for face recognition using multi-scale Weber local descriptors
(WLDs) and multi-level information fusion. Our method introduces the WLD, a novel and …

The influence of light changes makes the task of feature extraction more difficult for the local
descriptors. Most of local descriptors sacrifices their performance in harsh lightning …

This work suggests the 2 LBP variants so-called Neighborhood Difference LBP (ND-LBP)
and Neighborhood Mean LBP (NM-LBP). In ND-LBP, the comparison is conducted among …

This paper presents a novel approach in feature extraction, Local Symmetric Directional
Pattern (LSDP), for face recognition. The LSDP encodes the structure of facial textures …