Explore MATLAB source code curated for "图像识别" with clean implementations, documentation, and examples.
Implementation of grayscale conversion, histogram equalization, and median filtering for image preprocessing, enabling identification of landmark objects in images. Various sharpening methods are explored and compared, providing valuable learning resources for beginners in computer vision.
Image Recognition and Matching for Color Images with High Accuracy Rate and Fast Processing Speed, featuring algorithm explanations and key function descriptions
This repository contains MATLAB-based source code for image recognition with various practical examples demonstrating different techniques and algorithms.
Implementing feature extraction for videos or images using Hu moments, achieving excellent recognition performance through shape-based descriptors
A comprehensive collection of artificial intelligence algorithms covering various applications including function optimization, image recognition, and clustering. Implemented using MATLAB programming with included sample datasets for practical experimentation and validation.
MATLAB-based implementation for detecting and recognizing geometric shapes like circles, rectangles, and squares in digital images using image processing algorithms and pattern recognition techniques.
Application Background: This MATLAB-based learning resource focuses on HOG (Histogram of Oriented Gradients) and SIFT (Scale-Invariant Feature Transform) feature extraction methods. The SIFT implementation includes a ready-to-use match function for immediate deployment. Key Technologies: MATLAB programming environment with HOG and SIFT algorithms for image recognition and machine vision applications, featuring practical code implementation examples and algorithm explanations.
This MATLAB-based program implements the Local Binary Pattern (LBP) algorithm for image recognition applications, featuring texture feature extraction capabilities with practical code implementation details.
Image recognition and processing in MATLAB! High-quality program code with algorithm explanations!
This face recognition code utilizes wavelet decomposition for image processing, implementing pattern recognition through nearest neighbor classification method.