中英文资料对照翻译
(文档含英文原文和中文翻译)
英文原文
An Approach of Color Feature Evaluation in Color
Abstract—This paper analyzes 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 has 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 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 can 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
transform中文翻译
of RGB components. 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  components  of  RGB.  HSI  space  is  a  uniform  one  which 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 in 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 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 space.Color recognition technique has been applied to many fields  and  has  gone  ahead  rapidly.  For  instance,  color  recognition  in  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, YCbCr 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 suitable color space for obtaining a kind of valid color features t
o 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  named  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 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  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 is 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.
B.  CMY(CMYK) Color Space
CMY space is a spatial structure 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 aforementioned 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:
C.  YUV and YCrCb Color Space
YUV space and YCbCr space both generate a luminance component and two  chrominance components. In YUV space, Y is the luminance component, U and  V color difference. Y component is independent of the other two. Moreover, the YUV space can reduce the storage capacity required by digitalcolorful images by the  characteristic  of  human  vision.  In  YCbCr  space,  Y  is  the  luminance component, Cb is the blue color component and Cr the red color component. Its advantages  are  obvious  that  color  components  are  separated  from  luminance components  and  linear  transformation  can  be  performed  from  RGB  space. Transformation from RGB space to YUV space can beexplained approximated  by the following equations:
D.    HSI Color Space
HSI space is established from the human psychologicalperception point of view.  H  (hue)  is  a  color
  in  a  color  corresponding  to  the  main  wavelength  in chromatography. S (saturation) is equivalent to the purity of color. I (intensity ) is the brightness of color and the

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