SPARSE GLCM: GRAY-LEVEL CO-OCCURRENCE MATRIX COMPUTATION FOR POINT CLOUD PROCESSING
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United States of America
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Apr 3, 2025
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Jun 28, 2024
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Jun 28, 2024
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Abstract
A novel method of classifying point cloud data by extending the Gray-level Co-occurrence Matrix (GLCM) technique from the 2D to the sparse 3D domain is described herein. The method is able to be applied to point clouds derived from a mesh collection/meshes (such as, the Real-World Textured Things (RWTT) mesh collection). Implementations designed for multiple purposes are described herein: sampling and quantization of RWTT meshes, generation of GLCMs and corresponding texture descriptors, and the selection of potential candidate point clouds based on these extracted descriptors.
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