Illumination and Rotation Invariant Texture Representation
نویسندگان
چکیده
In this paper, we propose a new feature for texture representation that is based on pixel patterns and is independent of the variance of illumination and rotation. A gray scale image is transformed into a pattern map in which edges and lines used to characterize the texture information are classified by pattern matching. The Gabor filters can enhance edge features, however, are not effective in edge pattern classification. We extract the pattern templates from image patches by Principal Component Analysis (PCA). Based on the pattern maps, the feature vector is comprised of a sorted histogram. The calculation of the features is simple and computationally efficient compared with other illumination and rotation invariant texture schemes
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