MATLAB Implementation of LBP Feature Extraction

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Resource Overview

MATLAB implementation of LBP feature extraction with getmapping.m defining three different LBP patterns and lbp.m containing the core implementation using efficient sliding-window approach for whole-image LBP transformation without regional partitioning.

Detailed Documentation

This MATLAB implementation demonstrates Local Binary Pattern (LBP) feature extraction, a widely used method for capturing texture and structural information in images. The algorithm works by comparing each pixel with its neighbors to create binary patterns that characterize local texture features. The implementation includes getmapping.m which defines three distinct LBP operation modes (uniform, rotation-invariant, and basic patterns), while lbp.m contains the main algorithm that performs LBP transformation on the entire image using an efficient sliding-window approach. Although this version processes the whole image without regional partitioning, it cleverly employs matrix shifting operations to compute LBP values efficiently by circularly comparing central pixels with their 8-connected neighbors. The implementation effectively extracts texture features by converting local intensity relationships into binary codes that form histogram-based feature descriptors.

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