We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Local image descriptor developed from Fechner's law.
- Authors
Gao, Jun; Xu, Jie; Guo, Xuan; Deng, Yizhi; Feng, Jinxiang
- Abstract
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 (i.e., subjective sensation). Inspired by Fechner's law, we use the salient differences among pixels in images as the physical characteristics to mimic the human pattern perception and propose a Fechner local image descriptor (FLID) for face image representation. FLID is a nonlinear descriptor, so the represented image is more hierarchical than the general linear one. In addition, a threshold method is used to divide the features into four different intervals, which can effectively reduce the effects of noise and illumination. However, considering that FLID only extracts the local features of single-scale blocks, we incorporate multi-scale block into FLID and propose a multi-scale block Fechner local image descriptor (MB-FLID) to extract more global structural features. In the experimental part, we verified the performance of FLID and MB-FLID on the Face Recognition Technology (FERET), extended Yale-B, Olivetti Research Laboratories, Yale, and AR face databases, and compared them with a host of other local feature descriptors. The experimental results show that the proposed FLID and MB-FLID outperform the compared descriptors.
- Subjects
WEBER-Fechner law; DESCRIPTOR systems; HUMAN facial recognition software; IMAGE representation; VISUAL perception; GAZE
- Publication
Journal of Electronic Imaging, 2023, Vol 32, Issue 1, p13037
- ISSN
1017-9909
- Publication type
Article
- DOI
10.1117/1.JEI.32.1.013037