X-Ray Image Edge Detection Based on Wavelet Transform and Lipschitz Exponent

2009 ◽  
Author(s):  
Guowei Tang ◽  
Xiaoqing Zhong ◽  
Fangzhou Zhang ◽  
Zhenying Jin
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
X Ray ◽  
Lipschitz Exponent ◽  
Image Edge Detection ◽  
Image Edge

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.

Coal Gangue Image Edge Detection Based on Wavelet Transform

2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Coal Gangue ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Image Edge

An edge detection algorithm is developed for coal gangue images, and the method has two advantages compared with traditional ones. Firstly, multi-resolution analysis of wavelet transform can improve the quality of edge detection. Secondly, the algorithm is faster for real time. Since the threshold directly from the coefficients of wavelet transform, the rate of recognition for coal gangue is highly raised. The experiment results show that the method is an efficient edge detection algorithm for extraction edges from the noised images of coal gangues.

Algorithm for Improving Image Edge Detection Based on Directional Wavelet Transform

2014 ◽  
Vol 543-547 ◽  
pp. 2763-2765
Author(s):  
Xiang Shi Wang ◽  
Gui Feng Liu
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Median Filter ◽  
Image Data ◽  
Edge Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Directional Wavelet

The information of the image edge is the important parameters in identifying, segmenting and compressing image. The performance of the algorithms about edge image algorithms closely relies on the noises generally included in the image. The main goal of this paper is firstly to eliminate the false edges by the median filter and extract the information of the edge image by directional wavelet transform. Application on image data shows that the proposed tool can enhance the direction edge images which is fused to form the complete image edge.

Sign in / Sign up

Export Citation Format

Share Document