A physical Approach to Color Image Understanding

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A physical Approach to Color Image Understanding (1990)

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by Gudrun J. Klinker , Steven A. Shafer , Takeo Kanade

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211 - 10 self

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@MISC{Klinker90aphysical,
    author = {Gudrun J. Klinker and Steven A. Shafer and Takeo Kanade},
    title = {A physical Approach to Color Image Understanding},
    year = {1990}
}

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Abstract

In this paper, we present an approach to color image understanding that can be used to segment and analyze sur- faces with color variations due to highlights and shading. The work is based on a theory-the Dichromatic Reflec- tion Model-which describes the color of the reflected light as a mixture of light from surface reflection (highlights) and body reflection (object color). In the past, we have shown how the dichromatic theory can be used to separate a color image into two intrinsic reflection images: an image of just the highlights, and the original image with the highlights removed. At that time, the algorithm could only be applied to hand-segmented images. This paper shows how the same reflection model can be used to include color image segmentation into the image analysis. The result is a color image understanding system, capable of generating physical descriptions of the reflection processes occurring in the scene. Such descriptions include the intrinsic reflection images, an image segmenta- tion, and symbolic information about the object and highlight colors. This line of research can lead to based image understanding methods that are both more reliable and more useful than traditional methods.

Keyphrases

color image understanding physical approach intrinsic reflection image theory-the dichromatic reflec tion model-which dichromatic theory color variation object color original image surface reflection color image color image segmentation color image understanding system highlight color body reflection symbolic information reflected light traditional method image segmenta tion reflection model physical description image analysis analyze sur hand-segmented image

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