一种基于粗糙集的图像分类方法

提出一种基于图像内容的颜色特征并利用粗糙集进行分类的模型。粗糙集理论在数据分类应用中的主要思想是保持分类能力不变的情况下,利用等价类,通过属性约简和决策规则约简,达到挖掘知识并简化知识的目的。实验结果表明在图像分类方面,粗糙集方法性能良好,相对于贝叶斯方法更加准确和高效。

The Rough Set Based Approach for Image Classification

This paper presents a rough set based classification model for images with the color feature. The application of the rough set theory for image classification is to utilize equivalence relation classes through attribution reduction and decision rule reduction, and to obtain knowledge and the reduction of knowledge in the case of keeping the same ability for classification. Our Experiment shows that the rough set based approach can be well applied for image classification, and it is more efficient than the Bayesian approach.