Explore MATLAB source code curated for "识别" with clean implementations, documentation, and examples.
MATLAB implementation of the 2DLDA algorithm for face recognition, utilizing nearest neighbor classifier for identification with feature extraction and dimensionality reduction capabilities.
Implementation of LDA for face feature extraction and recognition using MATLAB, including code development and comprehensive result analysis with performance metrics
ICA-based feature extraction and recognition system with video processing components including binarization source code, frame-by-frame processing algorithms, and object tracking implementation. Features a master's thesis project on video gesture tracking and recognition, documented in comprehensive Word documentation with detailed code explanations.
This program implements feature extraction for input digit images, generating corresponding vector representations to facilitate subsequent recognition tasks. The implementation involves key computer vision algorithms for dimensionality reduction and pattern identification, typically utilizing techniques like HOG (Histogram of Oriented Gradients) or pixel intensity normalization to convert spatial image data into meaningful numerical features.
High-quality 1D barcode detection and recognition source code implementation with comprehensive algorithm explanations and key function descriptions, serving as an excellent reference for developers.
The system first utilizes "gettrainingdata" to extract facial features from the sample database where each individual has only one sample. Then "facerecognition" processes input faces for identification, delivering relatively accurate recognition results through feature matching algorithms.
Source code for a custom-built naive Bayes classifier implemented in MATLAB, suitable for classification and recognition tasks
The code in the file primarily implements functionalities including obstacle removal for occluded persons in images, image upscaling and enhancement, image denoising (mainly using wavelet denoising, wavelet decomposition denoising, and threshold-based denoising), facial feature extraction, height feature extraction, and finally person identification.
Fourier descriptors are used to describe and recognize the shapes of edged objects in images. This MATLAB-based program has been tested and verified as functional, implementing edge detection and Fourier transform algorithms for shape analysis.
This program implements color-based license plate localization using advanced computer vision techniques to accurately identify and extract license plate regions from vehicle images.