An image classification algorithm using fuzzy support vector machine

Cao Jianfang,Chen Junjie and C

Abstract

The development of electronic technology and imaging technology has resulted in the rapid growth of digital images. It has become an urgent problem to rely on advanced technology to identify images. An image recognition algorithm based on fuzzy support vector machine is proposed. The algorithm makes up for the lack of traditional support vector machine in multi-classification problems and solves the problem of semantic ambiguity in image classification by defining fuzzy membership function. Using 6 types of natural images to test, the experimental results show that classification performance improves significantly compared with the traditional support vector machine method.