Research on a Thangka Image Classification Method Based on Support Vector Machine

被引：7

作者：

Wang, Tiejun ^{[1
,2
]}

Wang, Weilan ^{[1
,2
]}

机构：

[1] Northwest Minzu Univ, Minist Educ, Key Lab Chinas Ethn Languages & Informat Technol, Lanzhou 730030, Gansu, Peoples R China

[2] Northwest Minzu Univ, Sch Math & Comp Sci, Lanzhou 730030, Gansu, Peoples R China

来源：

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2019年 / 33卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Thangka image; image classification; SVM; SVM;

D O I：

10.1142/S0218001419540302

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

As an art image, Thangka images have rich themes, various forms of expression, complex picture content and many layers of color representation. This paper mainly constructs a multicore support vector machine (SVM) based on the information entropy feature-weighted radial basis kernel function. In this paper, the kernel function is optimized, and the feature reduction is performed by using the random forest feature selection algorithm with average accuracy degradation. Finally, the effective classification of the icon image and the mandala image in Thangka is realized. The research results provide support for the follow-up study of Thangka image annotation and retrieval.

引用

页数：15

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