Explore MATLAB source code curated for "lbp" with clean implementations, documentation, and examples.
A MATLAB-based pedestrian detection system integrating HOG (Histogram of Oriented Gradients) and LBP (Local Binary Patterns) algorithms for improved feature extraction and classification accuracy.
MATLAB code for Local Binary Pattern (LBP) implementation featuring uniform patterns, rotation-invariant patterns, and rotation-invariant uniform patterns with detailed algorithm explanations and practical code implementation approaches.
A comprehensive face recognition system based on Local Binary Pattern (LBP) methodology, featuring subroutines for local binarization and histogram feature vector extraction. The system supports integration with face databases for testing recognition accuracy and demonstrates high recognition rates through robust algorithmic implementation.
Face recognition system implemented using the open-source Yale face database, employing Local Binary Patterns (LBP) for facial feature extraction and K-Nearest Neighbors algorithm for classifying facial feature vectors, achieving approximately 90% recognition accuracy with excellent performance results.
Implementing Local Binary Patterns (LBP) for block-based image segmentation enables microscopic feature enhancement through localized texture analysis
MATLAB implementation of pedestrian detection algorithm using HOG, LBP, and HIKSVM, including the libsvm-mat-3.0-1 package with comprehensive feature extraction and classification code.
MATLAB source codes for High-Pass Gaussian Filtering, Local Binary Patterns (LBP), and Local Derivative Patterns (LDP) for image enhancement and feature extraction applications.
Implementation of classic face recognition algorithms using AdaBoost, KNN, and LBP feature extraction with code explanations and technical insights
Comprehensive implementation of image preprocessing methods (grayscale enhancement, wavelet high-pass filtering, LBP, iterative threshold segmentation, seed growing method, etc.) combined with RGB and texture (co-occurrence matrix) feature extraction algorithms
The LBP function computes local binary pattern images or LBP histograms from input images, providing texture features for computer vision applications with configurable neighborhood parameters.