基于线性分类器的混合空间查找表颜色分类方法

提出了一种基于线性分类器的混合颜色空间查找表颜色分类方法,该方法主要解决颜色查找表分类方法的区分能力受颜色空间选择、阈值确定等因素影响而难以区分近似颜色的问题。将模式识别中的线性分类器思想应用于颜色查找表映射关系的建立,并通过同时使用HSI空间与YUV空间的方法提高查找表对近似颜色的区分能力。实验结果表明,基于线性分类器的混合空间查找表颜色分类方法具有查找表建立原则简单、效果直观的特点,并且对近似颜色有较强的区分能力,适用于彩色图像的快速颜色分割。

Linear Classifiers Based CLUT Classifying Method in Combined Color Space

This paper presents an improved CLUT color classification method based on linear classifiers and combined color space. The CLUT method is a useful method for color classification. However, the segmentation ability of CLUT is always weakened by the inaccurate choices of color space and threshold, especially when dealing with similar colors. Similar colors always have the almost same distributions in one color space, while have separate distributions in another color space. Combined color space can improve the ability to distinguish similar colors. Linear classifier is one of the most popular methods for pattern classification in pattern recognition. The principle of linear classifier is to use lines to separate the color spaces according to the distributions of different colors. The linear classifiers make it very convenient to set up the table and less depend on the experience of operators. The idea of linear classifiers is applied in this paper to build the CLUT. Meanwhile, HSI and YUV color spaces are employed to increase the ability to segment similar colors. The results of the experimentation show that the combined color space classification method, based on linear classifiers, is efficient and easy to establish look up table and to segment similar colors. The method can be applied to the fast segmentation of color image.