Explore MATLAB source code curated for "论文" with clean implementations, documentation, and examples.
Implementation of feature extraction in target recognition through Sparse Principal Component Analysis, including research paper and simulation code with detailed algorithmic explanations.
Camera calibration implementation with Zhang Zhengyou's algorithm, featuring complete MATLAB/OpenCV code, included research papers, and practical running examples
Implementing camera self-calibration parameter computation with genetic algorithms, accompanied by detailed MATLAB code and comprehensive paper documentation
A new active contour model algorithm that simplifies traditional implementation processes while improving performance. The associated paper "Active Contours Driven by Local Image Fitting Energy" was published in Pattern Recognition (2009). This approach enhances segmentation accuracy through localized energy minimization techniques.
This is a rare and hard-to-find resource featuring an algorithm and research paper on principal curve-based contour extraction, worth trying out! The implementation involves advanced curve fitting and feature detection techniques for robust image analysis.
Multi-focus Image Fusion Using Bilateral Gradient-based Sharpness Criterion corresponds to the paper by J. Tian, L. Chen, L. Ma and W. Yu, with implementation focusing on analyzing bilateral gradients to determine regional sharpness for fusion.
Recently published Kalman Filter research paper and MATLAB/Python implementation featuring detailed code comments, expert-reviewed methodology, and high-precision filtering algorithms suitable for academic and engineering applications.
The research content of this project includes: (1) Designing the overall architecture of the answer sheet recognition system, including system framework, hardware composition, and software development plan with primary focus on software implementation. (2) Determining digital image processing algorithms involving image preprocessing, tilt and rotation correction, and binary transformation. Through comparative analysis of multiple processing methods combined with image characteristics, Hough transform was selected for detecting line inclination angles in images followed by rotational correction. (3) Implementing identification of answer-marking areas and student ID regions using MATLAB software, achieving accurate extraction of student IDs and answers (both multiple-choice and single-choice questions) through optimized region detection algorithms.
Research on instantaneous frequency extraction technology using instantaneous phase method for linear frequency modulated signals, including MATLAB program implementation with detailed algorithm explanation and referenced research paper analysis
Comprehensive EEMD programs and research papers, including detailed usage methods, complete functionalities and tools for signal analysis and processing applications