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中文摘要：
电子技术和成像技术的发展导致数字图像迅速增长，依靠先进的技术识别和分类海量的图像数据正是当前各行业急需解决的问题。为此提出了一种基于模糊支持向量机的图像分类方法，通过定义模糊隶属度函数弥补了传统支持向量机在多分类问题中的不足，解决了图像分类中的语义模糊问题。使用Internet上的六类自然图像进行测试，实验结果表明，与传统的支持向量机方法相比，分类性能显著提高。
英文摘要：
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.
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