Explore MATLAB source code curated for "hough变换" with clean implementations, documentation, and examples.
A localization process for iris image processing utilizing binarization combined with Hough transform methodology to accurately identify iris regions, with implementation insights on thresholding techniques and circular detection algorithms.
Hough transform for line and circle detection with center and radius extraction implementation
MATLAB implementation of automated iris segmentation utilizing the Hough transform algorithm for edge detection and boundary extraction, designed for biometric recognition applications.
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.
Implementation of lane line detection using MATLAB's built-in Hough(), houghlines(), and houghpeaks() functions with parameter tuning for optimal performance
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
Hough Transform for circle detection with radius identification, capable of determining both unknown circle centers and radii through parameter space analysis
Practical MATLAB code implementation of Hough transform for robust detection of lines, circles, and ellipses in computer vision applications
Implementation of Hough Transform line detection algorithm based on the "Digital Image Processing" textbook by Gonzalez, featuring parameter space transformation and peak detection techniques.