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    外文翻译---关于颜色识别中颜色特征分析的方法

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    外文翻译---关于颜色识别中颜色特征分析的方法

    1、陕西科技大学 1 英文原文 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) An Approach of Color Feature Evaluation in Color Recognition Qi Xiaoxuan, Ji Jianwei School of Information & Electric Engineerin Shenyang Agriculture University Shenyang, China AbstractThis paper analy

    2、zes the characteristics of five commonly used color spaces and explores their influences on color recognition respectively. Divisibility evaluation based on distance criterion is utilized to evaluate the different colorfeatures in each color space and experimental results show that HSI color space h

    3、as the best divisibility performance. Keywords-color space;colorrecognition; feature evalutation; divisibility critiron I. I NTRODUCTION Color is the most intuitive vision feature to describe colorful images. It has been widely used in pattern recognition for the reason that color feature is almost

    4、free from the effects of scale, rotation and translation for the input images 1. Colors in colorful images can be defined by different color space models, such as RGB space, CMY space, I1I2I3space, YUV space and HSI space. Among the above color spaces, RGB is the basic and the most common one and ca

    5、n readily be mapped into other color spaces. However, RGB space is non-uniform for color perception and is too easily influenced by light. The three color components of RGB space are correlated with each other 2. CMY space represents colors by the complementary component of RGB components. YUV space

    6、, frequently used in color TV systems, uses three channels as Y, U and V to define the pixel. Y are the brightness information, U and V are the color difference which denotes the overall color difference instead of the difference between the three components of RGB. HSI space is a uniform one which

    7、consists to the human perception of colors. Its three components are mutually independent and can perceive color change of each component respectively. But non-linear transform in HSI space may lead substantial computation as well as singularity of the color space when the saturation is low. While i

    8、n YCbCr color space, the chrominance component and the luminance component are interdependent. Besides that, the conversion from YCbCr space to RGB space is linear and simple, so YCbCr space is commonly used in the field of video encoding compression. YUV space, YCbCr space and HSI space all represe

    9、nt spectrum in two dimension and use the third dimension to represent the intensity of color, which enables them more suitable for occasions where light intensity changes, than RGB space.Color recognition technique has been applied to many fields and has gone ahead rapidly. For instance, color recog

    10、nition in 陕西科技大学 2 product surface, license plates identification, face recognition and skin recognition 3-6. Color recognition effects differ with the change of color space. This paper investigates on color feature divisibility in the commonly used color spaces as RGB space, CMY space, YUV space, Y

    11、CbCr space, I1I2I3space and HSI space. Analysis indicates that HSI has the best divisibility performance in all the above color spaces based on the distance criterion. It provides a theory basis for color recognition. II. COLOR SPACE AND I TS T RANSFORMATION It is essential to build up and select a

    12、suitable color space for obtaining a kind of valid color features to characterize colorful images. Different color spaces are utilized for different research purposes. Color space means to define color by an array in three-dimension space. In the processing of colorful images, color space is also na

    13、med as color model or color coordinates. One color space can be converted to another by certain transforms. Below is the introduction of some color spaces and their conversions 7. A. RGB Color Space Red (R), green (G), blue (B) are three primary colors ofspectrum. All colors can be generated by the

    14、sum of the threeprimary colors. In digital images, values of R, G and B rangefrom 0 to 255. A cube in three-dimension coordinate space can be used to describe the RGB color space, where red, green andblue are the three axes, shown in Fig. 1.The main drawback of RGB color space as follows: It is not

    15、intuitive. It is difficult to see from the RGBvalues the cognitive attributes that the color representsitself. It is non-uniform. The perception difference betweentwo colors in RGB space is different from the distancebetween the two colors. It is dependent on hardware devices. In a word, RGB space i

    16、s device-related and an incompleteintuitive color description. To overcome these problems, othercolor spaces,which are more in line with characteristics of color vision, are adopted. RGB space can be mapped to other color spaces readily. 陕西科技大学 3 B. CMY(CMYK) Color Space CMY space is a spatial struc

    17、ture of a rectangular Cartesian. Its three primary components are cyan (C), magenta (M) and yellow (Y). Colors are obtained by subtractive colors. CMY space is widely used in non-emission display as inkjet printers. Equal amount of the three components can generate the black color. But the aforement

    18、ioned black color is not pure. Generally speaking, to generate true black color, the fourth component, i.e. black, is added in. This is the CMYK color space. CMY space is not very intuitive and non-linear. Its three components are the complementary colors of R, G and B. The transformations are as follows: The transformations from RGB space to CMY space are as follows:


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