外文翻譯---關(guān)于顏色識(shí)別中顏色特征分析的方法(已修改)
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【正文】 陜西科技大學(xué) 1 英文原文 2020 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 amp。 Electric Engineerin Shenyang Agriculture University Shenyang, China Abstract—This paper analyzes the characteristics of five monly 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 has the best divisibility performance. Keywordscolor 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 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 mon one and can readily be mapped into other color spaces. However, RGB space is nonuniform for color perception and is too easily influenced by light. The three color ponents of RGB space are correlated with each other [2]. CMY space represents colors by the plementary ponent of RGB ponents. YUV space, 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 ponents of RGB. HSI space is a uniform one which consists to the human perception of colors. Its three ponents are mutually independent and can perceive color change of each ponent respectively. But nonlinear transform in HSI space may lead substantial putation as well as singularity of the color space when the saturation is low. While in YCbCr color space, the chrominance ponent and the luminance ponent are interdependent. Besides that, the conversion from YCbCr space to RGB space is linear and simple, so YCbCr space is monly used in the field of video encoding pression. YUV space, YCbCr space and HSI space all represent 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 recognition technique has been applied to many fields and has gone ahead rapidly. For instance, color recognition in 陜西科技大學(xué) 2 product surface, license plates identification, face recognition and skin recognition [36]. Color recognition effects differ with the change of color space. This paper investigates on color feature divisibility in the monly used color spaces as RGB space, CMY space, YUV space, YCbCr space, I1I2I3space
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