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Detection of Textured Areas in Images Using a Disorganization Indicator Based on Component Counts
Bergman, Ruth; Nachlieli, Hila; Ruckenstein, Gitit
HPL-2005-175R1
Keyword(s): texture detection; texture analysis; texture synthesis; image analysis
Abstract: An algorithm is presented for the detection of textured areas in digital images. Texture detection has potential application to image enhancement, tone correction, defect detection, content classification and image segmentation. For example, texture detection may be combined with a color model and other descriptors to detect objects in an image, such as sky, which is generally smooth, and foliage, which is textured. The texture detector presented in this paper is based on the intuition that texture in a natural image is "disorganized". The measure we developed to detect texture examines the structure of local regions of the image. This structural approach enables us to detect both structured and unstructured texture at many scales. Furthermore, it distinguishes between edges and texture, and also between texture and noise. Automatic detection results are shown to match human classification of corresponding image areas.
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