【正文】 U Zhongwei, ZHANG Yujin, “A Comparitive and Analysis Study of Ten color Featurebased Image Retrieval Algorithms”,SIGNAL PROCESSING, , , 2020. [9] Liu Jin, Chen Gi, Yu Ruizhao, “Development of Computer Color Science”, COMPUTER ENGINEERING,2,1997. [10] YANG recognition and Intelligent Computation: Matlab Technolgoy, Beijing: Electronic Industry Press, 2020. 陜西科技大學(xué) 9 中文譯文 2020 第八屆模糊系統(tǒng)與知識挖掘國際學(xué)術(shù)會議（ FSKD） 關(guān)于顏色識別中顏色特征分析的方法 紀(jì)建偉 齊曉軒 信電與電氣工程學(xué)院 沈陽農(nóng)業(yè)大學(xué) 沈陽，中國 摘要：分析五種常用的顏色空間的特征并研究其分別對顏色識別的影響。本文通過研究 RGB 空間， CMY 空間， YUV 空間， YCbCr 空間， I1I2I3 空間及 HSI空間這幾個常用顏色空間的顏色特征可除性，得出結(jié)論：在上述基于距離判據(jù)的顏色空間中， HSI 最具可除性；并為顏色識別提供理論基礎(chǔ)。 B． CMY(CMYK)顏色空間 CMY 空間是笛卡爾直角坐標(biāo)系的空間結(jié)構(gòu)，其三個主要組件是青色（ C），品紅（ M），黃色（ Y）。顏色空間的有效性是處 理彩色圖像的關(guān)鍵，可除性標(biāo)準(zhǔn)則被用來檢測不同顏色空間對顏色的分類。 感謝 本項目由遼寧省自然科學(xué)基金資助（項目編號： 20202153）。 陜西科技大學(xué) 11 通過顏色空間，抽象、主觀的視覺感知可被轉(zhuǎn)化為三維空間中的特定位置、矢量，從而有可能使彩色圖像和設(shè)備的顏色特征可視化。 3. 依賴于硬件設(shè)備 總之， RGB 空間與設(shè)備相關(guān)，是一個不完備的直觀顏色說明。顏色識別技術(shù)現(xiàn)已被應(yīng)用于各項領(lǐng)域，發(fā)展迅速；如產(chǎn)品表面，汽車牌照定位，人臉及皮膚紋理識別【 36】。 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, licen