Abstract：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.