Run-Length Encoding for Volumetric Texture

D.-H. Xu, A.S. Kurani, J.D. Furst, and D.S. Raicu (USA)


Image processing and analysis, volumetric texture, run length encoding, and texture features.


With the dramatic increase of 3D imaging techniques, there is a great demand for new approaches in texture analysis of volumetric data. In this paper, we present a new approach for volumetric texture analysis using a run length encoding matrix and its texture descriptors. We experiment with our approach on the volumetric data generated from two normal Computed Tomography (CT) studies of the chest and abdomen. Our preliminary results show that there are run-length features calculated from the volumetric run-length matrix that are capable of capturing the texture primitives' properties for different structures in 3D image data, such as the homogeneous texture structure of the liver.

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