Enhanced K-Means Algorithm for Image Processing
Implementation of an improved K-means algorithm for image processing applications with enhanced segmentation capabilities
mpiv: Particle Image Velocimetry Full-Field Velocity Analysis Code
A comprehensive MATLAB-based code for extracting full-field velocity measurements using Particle Image Velocimetry (PIV). This implementation includes image preprocessing, cross-correlation analysis, and post-processing routines to efficiently compute velocity fields from particle image pairs. Features automated processing pipelines with configurable parameters for different experimental setups.
Digital Image Processing Series
Program code implementations covering fundamental image processing techniques including: P0401 - Edge detection using Prewitt operator, P0402 - Edge detection with LoG operators at different σ values, P0403 - Edge detection using Canny operator, P0404 - Image threshold segmentation, P0405 - Image segmentation via watershed thresholding, P0406 - Matrix quadtree decomposition, P0407 - Text/non-text image classification, P0408 - Binary image edge detection using morphological gradient, P0409 - Morphological case study: removing PCB traces while preserving chip components.
Research on Vehicle Traffic Counting Using Area-Based Method
This paper focuses on studying area-based methods for vehicle traffic counting. The research algorithm development involves fundamental image processing techniques for vehicle detection including grayscale conversion, filtering, image enhancement, and sharpening, with comparative analysis of their algorithmic implementations. The study further employs image segmentation technologies such as threshold segmentation, edge detection, and morphological operations, along with vehicle detection and extraction algorithms. Finally, a real-time and reliable counting algorithm is designed.
Image Smoothing Processing
Image smoothing effectively removes noise interference, and when combined with sharpening techniques, it can significantly enhance image quality with proper implementation using filters and algorithms.
Road Surface Crack Detection and Identification System Design
This experimental demonstration showcases the application of image processing-based crack detection technology. Addressing the characteristics of road cracks including branching patterns, fine discontinuities, irregular distribution, and low contrast, the system implements a series of image preprocessing steps to highlight crack target regions. The implementation enhances automation levels for road surface inspection through GUI-based software module integration and data persistence using database storage, demonstrating considerable versatility across different scenarios.
Wavelet Transform-Based Compressed Sensing Image Processing with Three Reconstruction Algorithms
An implementation of compressed sensing image processing using wavelet transforms, featuring three distinct reconstruction algorithms with code-level explanations.
Implementing Image Pseudocolor Processing Using Gray Level Transformation and Frequency Domain Filtering Methods
Implementing image pseudocolor processing through gray level transformation and frequency domain filtering methods with MATLAB programming implementation, including algorithm explanations and key function descriptions
MATLAB Code Implementation for Image Processing
MATLAB image processing techniques covering histograms, image transforms, spatial filtering (image enhancement using templates), and edge detection operators with practical code implementations.
Image Processing Implementation with MATLAB Code
A comprehensive image processing application providing fundamental functionalities including multiple binarization algorithms, edge detection, image segmentation, and noise reduction. Features a practical license plate recognition case study with detailed code implementation insights.