A Novel Local Human Visual Perceptual Texture Description with Key Feature Selection for Texture Classification

Jianning Chi, Xiaosheng Yu, Yifei Zhang and Huan Wang

Mathematical Problems in Engineering, 2019, vol. 2019, 1-20

Abstract:

This paper proposes a novel local texture description method which defines six human visual perceptual characteristics and selects the minimal subset of relevant as well as nonredundant features based on principal component analysis (PCA). We assign six texture characteristics, which were originally defined by Tamura et al., with novel definition and local metrics so that these measurements reflect the human perception of each characteristic more precisely. Then, we propose a PCA-based feature selection method exploiting the structure of the principal components of the feature set to find a subset of the original feature vector, where the features reflect the most representative characteristics for the textures in the given image dataset. Experiments on different publicly available large datasets demonstrate that the proposed method provides superior performance of classification over most of the state-of-the-art feature description methods with respect to accuracy and efficiency.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2019/3756048.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2019/3756048.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3756048

DOI: 10.1155/2019/3756048

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().