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Neighborhood Rank Order Coding for Robust Texture Analysis and Feature Extraction
Kaiserslautern, Germany September 17-September 19
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HIS.2007.127th International Conference on Hybri ...
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Christian Mayr, University of Technology Dresden
Rene Schuffny, University of Technology Dresden
Research into the visual cortex and general neural information processing has led to various attempts to integrate pulse computation schemes in image analysis systems. Of interest is especially the robustness of representing an analogue signal in the phase or duration of a pulsed, quasi-digital signal, as well as the possibility of direct digital interaction, i.e. computation, among these signals. Such a computation can also achieve information compaction for subsequent processing stages. By using a pulse order encoding scheme motivated by dendritic pulse interaction, we will show that a powerful low-level feature and texture extraction operator, called Pulsed Local Orientation Coding (PLOC), can be implemented. Feature extraction results are being presented, and a possible VLSI implementation is detailed.
Citation:
Christian Mayr, Rene Schuffny, "Neighborhood Rank Order Coding for Robust Texture Analysis and Feature Extraction," his, pp.290-301, 7th International Conference on Hybrid Intelligent Systems (HIS 2007), 2007
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