scholarly journals Admissible Perturbation of Demicontractive Operators within Ant Algorithms for Medical Images Edge Detection

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 1040
Author(s):  
Cristina Ticala ◽  
Ioana Zelina ◽  
Camelia-M. Pintea
Keyword(s):  
Edge Detection ◽  
Medical Images ◽  
Positive Influence ◽  
Edge Information ◽  
Admissible Perturbation ◽  
The Matrix ◽  
Image Edge ◽  
Demicontractive Operator ◽  
Artificial Pheromone

Nowadays, demicontractive operators in terms of admissible perturbation are used to solve difficult tasks. The current research uses several demicontractive operators in order to enhance the quality of the edge detection results when using ant-based algorithms. Two new operators are introduced, χ -operator and K H -operator, the latter one is a Krasnoselskij admissible perturbation of a demicontractive operator. In order to test the efficiency of the new operators, a comparison is made with a trigonometric operator. Ant Colony Optimization (ACO) is the solver chosen for the images edge detection problem. Demicontractive operators in terms of admissible perturbation are used during the construction phase of the matrix of ants artificial pheromone, namely the edge information of an image. The conclusions of statistical analysis on the results shows a positive influence of proposed operators for image edge detection of medical images.

scholarly journals Sensitive Ant Algorithm for Edge Detection in Medical Images

2021 ◽  
Vol 11 (23) ◽  
pp. 11303
Author(s):  
Cristina Ticala ◽  
Camelia-M. Pintea ◽  
Oliviu Matei
Keyword(s):  
Edge Detection ◽  
Medical Images ◽  
Medical Diagnostics ◽  
Detection Methods ◽  
X Rays ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
The Stability ◽  
Artificial Pheromone

Nowadays, reliable medical diagnostics from computed tomography (CT) and X-rays can be obtained by using a large number of image edge detection methods. One technique with a high potential to improve the edge detection of images is ant colony optimization (ACO). In order to increase both the quality and the stability of image edge detection, a vector called pheromone sensitivity level, PSL, was used within ACO. Each ant in the algorithm has one assigned element from PSL, representing the ant’s sensibility to the artificial pheromone. A matrix of artificial pheromone with the edge information of the image is built during the process. Demi-contractions in terms of the mathematical admissible perturbation are also used in order to obtain feasible results. In order to enhance the edge results, post-processing with the DeNoise convolutional neural network (DnCNN) was performed. When compared with Canny edge detection and similar techniques, the sensitive ACO model was found to obtain overall better results for the tested medical images; it outperformed the Canny edge detector by 37.76%.

scholarly journals Effect of morphological algorithms on medical imaging

2021 ◽  
Vol 8 (3) ◽  
pp. 1-8
Author(s):  
Cuong Phan Viet ◽  
Thao Ho Thi ◽  
Anh Le Tuan ◽  
Ha Nguyen Hong ◽  
Thanh Ha Quang
Keyword(s):  
Medical Imaging ◽  
Edge Detection ◽  
Medical Images ◽  
Computer Software ◽  
Diagnosis And Treatment ◽  
Detection Methods ◽  
Morphological Operators

Handling and improving the quality of medical images with the help of computer software is one of the important stages in the diagnosis and treatment. In this article, we focus on describing the new morphological algorithms by ITK (Insight Segmentation and Registration Toolkit). These morphological operators eliminate noise, detect good edges, and overcome the drawback of traditional edge detection methods.

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.

Sub-Pixel Edge Detection of Color Image Based on Dimensionality Reduction Technique and Curve Fitting

2013 ◽  
Vol 433-435 ◽  
pp. 281-287
Author(s):  
Feng Xiao ◽  
Li Na Guo
Keyword(s):  
Edge Detection ◽  
Dimensionality Reduction ◽  
Curve Fitting ◽  
Color Image ◽  
Edge Information ◽  
Projected Image ◽  
Image Edge Detection ◽  
Dimensionality Reduction Technique ◽  
Image Edge ◽  
Edge Detection Method

In order to solve the problem of the color characteristic information is often ignored in color image edge detection process, we propose a new color image sub-pixel edge detection method, which uses Ostu algorithm to get coarse positioning edges and extracts sub-pixel edge on the combination of curve fitting and coarse positioning edge in the projected image obtained by dimensionality reduction technique.Experimental results show that the algorithm positioning accuracy can reach 0.14 pixels,it is able to extract color image edge information effectively.

Contents Based Color Image Edge Detection Using Hessian Matrix

2013 ◽  
Vol 427-429 ◽  
pp. 1853-1860 ◽  
Author(s):  
Li Zhang ◽  
Lie Jun Wang ◽  
Sen Hai Zhong ◽  
Gang Zhao
Keyword(s):  
Edge Detection ◽  
Color Image ◽  
Hessian Matrix ◽  
Edge Information ◽  
Image Edge Detection ◽  
Background Texture ◽  
Image Edge ◽  
Visual Characteristics ◽  
Direction Information ◽  
Pseudo Color

The edges are the most fundamental and important characteristic of an image, edge detection is the key link and classic topic in machine vision and image processing. Considering the human visual characteristics, the intrinsic gradient direction information of color images was used to obtain the pseudo-color edges of the images by conducting multichannel edge detection. After enhancing the edge information and removing the correlation, the brightness is extracted in order to obtain complete image edge information. To make the edges more smooth and continuous, the Hessian matrix is used to remove coarse edges and edges with redundant background texture. The experiment verifies the effectiveness of the proposed algorithm, and the comparison with other scheme indicates that our scheme can improve the effectiveness, continuity and sharpness of edge detection.

Based on Wavelet Transform and Fuzzy Algorithm of Coal Storage Image Edge Detection Algorithm

2011 ◽  
Vol 301-303 ◽  
pp. 1305-1309
Author(s):  
Bin Qu ◽  
Yan Jun Zhao ◽  
Cheng Yuan Bai
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Good Effect ◽  
Fuzzy Membership Function ◽  
Edge Detection Algorithm ◽  
Image Edge ◽  
Edge Detection Method ◽  
Modulus Maxima ◽  
Single Pixel

Volume and the coal quality of coal measure concerns cost accounting, economic benefit assessment work, when we determine the volume of coal, the camera will be used to obtain image information, and then mosaics and fitting the images, get the clear single pixel level profile. Which obtained a clear outline of a single pixel line is critical important for image fitting.This paper introduced Mallat wavelet modulus maxima edge detection method and fuzzy membership function constructed corresponding algorithm of single pixel level, get edge detection algorithm can obtain good effect.

A WAVELET-BASED IMAGE EDGE DETECTION AND ESTIMATION METHOD WITH ADAPTIVE SCALE SELECTION

2010 ◽  
Vol 08 (03) ◽  
pp. 385-405 ◽  
Author(s):  
SHEN SHI ◽  
YANNING ZHANG ◽  
YUENING HU
Keyword(s):  
Edge Detection ◽  
Multiple Scales ◽  
Estimation Method ◽  
Edge Point ◽  
Edge Information ◽  
Detection Scheme ◽  
Image Edge Detection ◽  
Singularity Type ◽  
Edge Detectors ◽  
Image Edge

A scale-adaptive edge detection scheme based on wavelet transform is proposed in this paper. This scheme incorporates the edge information in multiple scales of the wavelet domain, and it not only locates the position of each edge point, but also estimates its amplitude and identifies its singularity type, namely, step edge and ridge edge. Moreover, for a ridge edge point, the proposed scheme could estimate the width of the ridge. Unlike traditional edge detectors, this method adaptively selects two optimal scales for each edge point to locate it and estimate its direction. As a result, better performances in localization and edge direction estimation are achieved. Experiments on both synthetic and real images demonstrate the effectiveness of the proposed method.

scholarly journals Optimal Method of Vision Sensor Digital Image Edge Detection for Commercial Investment in Film Field

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zheng Liu
Keyword(s):  
Edge Detection ◽  
Digital Image ◽  
Film Industry ◽  
Rapid Development ◽  
Visual Sensor ◽  
Optimal Method ◽  
Sound Effects ◽  
Image Edge Detection ◽  
Image Edge

With the rapid development of the national economy, the film industry has risen rapidly under these conditions, and the development of film occupies a more important position in this process, which has led to the development of investment in the film field, an internationally recognized cultural space. This paper studies the commercial investment in the film field based on the edge detection of the digital image of the visual sensor. The purpose of the research is to point out the direction of commercial investment in the film industry by studying the effect of the edge detection of the digital image of the visual sensor on the application of the film object. The image edge detection algorithm based on wavelet transform and morphology and the application of these image edge detection algorithms such as wavelet theory analyze the shortcomings of movie, sound effects, and pictures and make a comparison before and after the improvement. Audiences, as the direct enjoyers of the cultural product of the film, their opinions, and evaluations of the film, largely determine the quality of the work. On the contrary, a good work can attract the public’s attention and bring a large impact. The data acquisition in this process is mainly based on the questionnaire survey of the audience. The experimental results show that before applying digital image edge detection to transform the clip, 7 people thought that the clip needed to be further improved to improve the quality of the film itself, and only 1 person affirmed the film; after the modification, 9 people proposed the film praise; in addition, 15 people audience watched the film processed by the edge detection method and gave high evaluations to the three aspects of sound effects, special effects, and editing, especially the editing part, with a score of 8.9.

scholarly journals Edge Detection technique based on HDR image quality assessment

2021 ◽  
Vol 2078 (1) ◽  
pp. 012029
Author(s):  
Dingxian Wang
Keyword(s):  
Image Quality ◽  
Edge Detection ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Edge Information ◽  
Image Edge Detection ◽  
Image Edge ◽  
Hdr Image

Abstract Image edge detection is one of the major study aspects in current computer image processing field. The quality of the input images is uneven, some have large fuzzy areas, some are underexposed, and the edges of objects in the images are difficult to detect, and the application scenarios of image edge detection are limited. In the view of the above problems, this paper has proposed that by applying High Dynamic Range (HDR) image quality assessment technology, combining multiple images with different exposures into one HDR image with detailed edge information, This technology effectively solved problem of low edge information richness, improved the effectiveness of edge detection algorithms, and contributed to the development of edge detection technology.

Improvement on Image Edge Detection Using a Novel Variant of the Ant Colony System

2019 ◽  
Vol 28 (05) ◽  
pp. 1950080 ◽  
Author(s):  
Karima Benhamza ◽  
Hamid Seridi
Keyword(s):  
Edge Detection ◽  
Local Variation ◽  
Ant Colony ◽  
Ant Colony System ◽  
Edge Information ◽  
Image Edge Detection ◽  
Artificial Ants ◽  
Novel Variant ◽  
Image Edge ◽  
Evaluation Parameters

In this paper, an improved Ant Colony System algorithm applied to image edge detection is presented. During their movement on image, artificial ants establish pheromone graph which represents the image edge information. The ant movement is directed by the local variation of the image’s intensity values. To improve this method, supplementary behaviors are added to each ant in response to its local stimuli, i.e., the ant self-reproduces and directs its progenitors to an appropriate direction to explore more suitable areas. Moreover, it dies if it exceeds a specific iteration age and so the ineffective searches are eliminated. These additional behaviors allow diversifying the exploration performed by ants and also reinforcing the exploitation of these ants’ search experience. Proposed approach allows having more accurate and more complete edges. The performance is tested visually with various images and empirically with evaluation parameters.

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