scholarly journals Application Of Image Edge Detection In Underwater High Speed Vehicle Classification

2017 ◽  
Author(s):  
Sen Wang ◽  
Qijun Liu ◽  
Jiaxing Qiu
Keyword(s):  
Edge Detection ◽  
High Speed ◽  
Vehicle Classification ◽  
Image Edge Detection ◽  
Image Edge ◽  
High Speed Vehicle

scholarly journals A novel edge detection method based on efficient gaussian binomial filter

2021 ◽  
Vol 7 (2) ◽  
pp. 211
Author(s):  
El Houssain Ait Mansour ◽  
Francois Bretaudeau
Keyword(s):  
Edge Detection ◽  
High Speed ◽  
Detection Method ◽  
Detection Methods ◽  
Gaussian Filter ◽  
Image Edge Detection ◽  
Low Pass ◽  
Image Edge ◽  
Edge Detection Method ◽  
Low Pass Filters

Most basic and recent image edge detection methods are based on exploiting spatial high-frequency to localize efficiency the boundaries and image discontinuities. These approaches are strictly sensitive to noise, and their performance decrease with the increasing noise level. This research suggests a novel and robust approach based on a binomial Gaussian filter for edge detection. We propose a scheme-based Gaussian filter that employs low-pass filters to reduce noise and gradient image differentiation to perform edge recovering. The results presented illustrate that the proposed approach outperforms the basic method for edge detection. The global scheme may be implemented efficiently with high speed using the proposed novel binomial Gaussian filter.

New image edge detection model based on fractional-order partial differention

2013 ◽  
Vol 32 (10) ◽  
pp. 2848-2850
Author(s):  
Wei JIANG ◽  
Zhi-quan DING ◽  
Ya-wei LIU
Keyword(s):  
Edge Detection ◽  
Fractional Order ◽  
Detection Model ◽  
Model Based ◽  
Image Edge Detection ◽  
Image Edge

Local Adaptive Perceptual Color Difference for Color Image Edge Detection

2013 ◽  
Vol 34 (9) ◽  
pp. 2058-2063
Author(s):  
Xian Yang ◽  
Bo Li ◽  
Wen Ding ◽  
Qi-mei Chen
Keyword(s):  
Edge Detection ◽  
Color Image ◽  
Color Difference ◽  
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.

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