Application of Self-Organizing Maps to Texture Visualization and Analysis
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Abstract
The analysis of visual texture occupies a central role in many areas of computer vision. Applications of this technology include product inspection, medical image analysis, and analysis of remotely sensed data, such as satellite images of the Earth. Standard approaches to texture analysis generate a large number of statistics which are difficult to intuitively visualize. We explore the application of SelfOrganizing Maps (SOM), a type of artificial neural network, to visualizing these texture descriptors.
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