Research On Texture Image Statistics And Its Applications

Texture is one of the main research topics in computer vision. However, there exist many unsolved texture-related problems. One of those underlying problems is texture perception. The study of the visual perception of texture can help us to better understand the basic mechanisms of human vision and the impact of texture itself, and also illumine us to develop deeper researches on texture analysis and the corresponding applications. By virtue of statistical analyses on texture image and texture features, this thesis, in both the theoretical perspective and the practical perspective, probes into the visual perception of texture and such related problems as texture classification/segmentation, texture synthesis, and texture-based motion segmentation. The main contributions of this thesis are summarized as follows:(1) A texture in this thesis is treated as the superposition of the basic visual elements, which are learned from the observed texture image by the topographical independent component analysis (TICA). Those basic elements are expressed as matrices. The form of matrix for visual element has the ability to represent any type of natural textures. Based on the learned results, an approach of extracting visitons is proposed. Visitons are the representatives of those visual elements in the observed texture image, which provide a visual cue to research texture perception. Further, the number of visitons is defined as the intrinsic visual dimension. The larger the dimension is, the more the visual patterns emerge.(2) A new method for texture segmentation by using the learned TICA unmixing bases as filters is implemented. Experiments on mosaic texture images show the segmenting results are satisfactory.(3) This thesis develops the new research direction about global properties of textures. Based on the analysis of the global properties, this thesis finds that there exits distinct difference between texture images and natural images. It provides a proof in the statistical earning perspective for the fact that the most important measures for texture perception are periodicity, direction, and randomness. By virtue of the study on the relationships between natural images and texture images, ontology is introduced to analyze texture knowledge. The research tasks, the technical routes of texture ontology, and the relationship between its father ontology are also discussed.(4) A novel algorithm of identifying texture is proposed based on the commonly...