Color texture models for machine vision

We develop a physical model that characterizes the appearance of textured color surfaces in three dimensions. The model is derived from properties of surfaces and the physics of image formation. The color texture model describes the dependence of the spatial correlations within and between bands of a color image on surface reflectance, illumination, and the scene geometry. We show that there are important advantages in using color information for texture analysis. From our model, we derive an algorithm for recognizing instances of color textures independent of scene geometry. This algorithm is useful for the recognition of three dimensional objects and the segmentation of color images of three dimensional scenes. Experimental results are provided to confirm the model and to illustrate the performance of the algorithm.

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