Research on improved image edge detection based on Hough transform

2021 ◽  
Author(s):  
Long Cheng ◽  
Jian Fang ◽  
Yue Wu ◽  
Kai Kang
Keyword(s):  
Edge Detection ◽  
Hough Transform ◽  
Image Edge Detection ◽  
Image Edge

A Circle Contour Measurement Technique Based on Randomized Hough Transform Using Gradient Information

2005 ◽  
Vol 295-296 ◽  
pp. 277-282
Author(s):  
Ji Wen Cui ◽  
Jiu Bin Tan
Keyword(s):  
Edge Detection ◽  
Hough Transform ◽  
Fundamental Principle ◽  
Least Square ◽  
Detection Accuracy ◽  
Image Edge Detection ◽  
Randomized Hough Transform ◽  
Fitting Algorithm ◽  
Image Capturing ◽  
Image Edge

Hough Transform (HT) is an image edge detection technique which is widely used in pattern recognition and computer vision. In this paper the fundamental principle of HT is analyzed and the defect of HT and Randomized Hough Transform (RHT) is indicated. An algorithm based on RHT and the information of grayscale and gradient in image is proposed. It uses the property of the pattern and is mainly used for detection of circle and arc contour measurement. This algorithm can decrease memory usage in computer by a multi to one mapping, accelerate the calculation speed by parallel algorithm, improve the edge detection accuracy by subpixel division, obtain the parameters of object by applying least square fitting algorithm. Based on the principle, a measurement system with high accuracy and efficiency in image capturing and processing is developed. Experiments are carried out in the system. The result of experiment has certified the feasibility and validity of the algorithm.

scholarly journals Enhancing Ant-Based Algorithms for Medical Image Edge Detection by Admissible Perturbations of Demicontractive Mappings

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 885
Author(s):  
Vasile Berinde ◽  
Cristina Ţicală
Keyword(s):  
Edge Detection ◽  
Medical Image ◽  
Test Functions ◽  
Head Ct ◽  
X Ray ◽  
Numerical Tests ◽  
Image Edge Detection ◽  
Evaluation Of Parameters ◽  
Image Edge ◽  
Demicontractive Mappings

The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a recent paper by the second author and her collaborators, where they used admissible perturbations of demicontractive mappings as test functions. To illustrate this fact, we first consider some typical properties of demicontractive mappings and of their admissible perturbations and then present some appropriate numerical tests to illustrate the improvement brought by the admissible perturbations of demicontractive mappings when they are taken as test functions in ant-based algorithms for medical image edge detection. The edge detection process reported in our study considers both symmetric (Head CT and Brain CT) and asymmetric (Hand X-ray) medical images. The performance of the algorithm was tested visually with various images and empirically with evaluation of parameters.

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