Neighborhood Rank Order Coding for Robust Texture Analysis and Feature Extraction

TL;DR

This paper introduces a novel pulse order encoding scheme inspired by neural dendritic interactions, enabling robust texture analysis and feature extraction through the Pulsed Local Orientation Coding (PLOC) method, with potential for efficient hardware implementation.

Contribution

The paper presents a new pulse order encoding scheme for texture analysis, demonstrating its effectiveness and detailing a possible VLSI implementation.

Findings

Effective texture and feature extraction using PLOC

Robustness of pulse order encoding in image analysis

Potential for hardware acceleration with VLSI design

Abstract

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.