Explore MATLAB source code curated for "边缘提取" with clean implementations, documentation, and examples.
License plate recognition system utilizing Sobel operator for edge detection to extract Arabic numerals from license plates, enabling accurate character identification through digital image processing techniques.
Extract edges from an image and implement Hough transform to detect circular patterns in the image with code-based methodology
A versatile edge detection function capable of implementing Sobel, Prewitt, Roberts, Marr, and Canny operators through parameter configuration. Includes comprehensive design documentation with algorithm explanations and implementation details.
Experimental report on medical image segmentation (with source code) featuring: comparative analysis of edge detection using various operators (Sobel, Prewitt, Roberts, Laplacian); threshold-based segmentation; and segmentation discussion using watershed method with implementation insights.
MATLAB-based image processing edge detection program featuring multiple classic algorithms including Sobel, Canny, and Prewitt operators with configurable parameters.
The provided files contain multiple MATLAB programs for image processing, including implementations for image segmentation and edge detection algorithms. These scripts demonstrate practical approaches to common computer vision tasks.
Implementation using MATLAB: Wavelet modulus maxima for edge extraction. Simulation performed on the standard 'woman' image from MATLAB's image processing toolbox, with result visualization demonstrating the effectiveness of modulus maxima in edge detection through wavelet transform analysis.
Implementation of background subtraction for detecting moving vehicles, including image preprocessing and edge extraction techniques for vehicle images
Application Background: Gabor filter serves as a linear filter for edge detection in image processing, with frequency and directional responses similar to the human visual system. Research shows Gabor filters excel in texture representation and separation, consisting of Gaussian kernel functions modulated by sinusoidal plane waves in the spatial domain. Technical Approach: Comparative analysis of PCA dimensionality reduction examples reveals consistent methodology - extracting covariance matrices from original data, computing eigenvectors/eigenvalues, and generating transformation matrices through KL transformation based on eigenvalue-sorted eigenvectors.
The SUSAN algorithm is a grayscale feature point-based method used for image edge extraction, which identifies edge positions by detecting distinct grayscale features in images.