Explore MATLAB source code curated for "直线检测" with clean implementations, documentation, and examples.
Efficient line detection in grayscale images using the Fast Hough Transform algorithm, featuring accurate endpoint localization with experimental result visualization and implementation insights.
This MATLAB code implements standard Hough Transform for detecting lines in binary images, demonstrating the working mechanism of this fundamental computer vision technique. The implementation uses polar coordinate representation and accumulator arrays to identify linear patterns.
Implementation of line detection via Hough transform constructs a target line segment with 2 signal-to-noise ratio and 34-pixel length in Gaussian-distributed noise background; after identifying the line equation, a fixed-length sliding window approach determines segment endpoints to precisely locate the line segment position. Algorithm includes Hough voting mechanism and peak detection for parameter space analysis.
Detection of lines, circles, and ellipses using Hough Transform methodology, with line detection implemented in VC++ code and circle/ellipse detection implemented in MATLAB code, featuring robust parameter space analysis for shape recognition in digital images.
Implementation of line detection in grayscale images through Hough transform with parameter optimization and OpenCV integration
The Hough function-based line detection program offers excellent performance with adjustable internal parameters for optimal results, enabling robust image analysis and shape recognition.
This algorithm employs the Hough transform for straight-line detection of lane markings, with implementation details including edge detection preprocessing and parameter space optimization.
MATLAB-based Remote Sensing Road Extraction with Hough Detection Algorithm Implementation
Standard Hough Transform