An analysis of grating cell features for texture discrimination
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The design of artificial vision systems has been influenced by knowledge of the early stages of processing in the human vision system. The discovery of directionally sensitive cells in the human visual cortex lead to the theory of edge detection in computer vision, and the discovery that simple cell receptive fields can be modeled as Gabor filters has led to the development and use of Gabor jets. In this thesis, we evaluate a low-level image feature inspired by “grating” cells found in the human visual cortex. These cells, and the features based on them, detect spatial gratings–repeated patterns of light and dark bars–in their receptive fields. We evaluate the utility of grating cell model features to distinguish different textures using Fisher’s linear discriminant. It will be shown that the grating cell features contain significantly more distinguishing information than another standard Gabor-filter-based image feature.