Open AccessImage texture model based on energy features
Author(s) -
Maya M. Lyasheva,
Stella A. Lyasheva,
Mikhail P. Shleymovich
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1902/1/012120
Subject(s) - pixel , artificial intelligence , computer vision , computer science , texture (cosmology) , wavelet , energy (signal processing) , image texture , pattern recognition (psychology) , set (abstract data type) , texture filtering , image (mathematics) , representation (politics) , image processing , point (geometry) , wavelet transform , mathematics , statistics , geometry , politics , political science , law , programming language
In information processing and control systems based on computer vision technologies, it is necessary to provide an effective indicative representation of images for their subsequent analysis. One of the widely used approaches is based on the construction of texture models. In this paper, the description of the texture using energy features is considered. The proposed model is a set of weights of image pixels reflecting their significance from the point of view of image perception. The significance of the pixel is estimated using the energy of the coefficients of the orthogonal discrete multiresolution wavelet transform. The paper presents expressions for calculating pixel weights and shows that the resulting texture models can be used to classify images.