Image Edge Detection Based on Ant Colony Optimization Algorithm

نویسنده

  • Yin Huan
چکیده

No part of this journal may be reproduced or used in any form or by any means without written permission from the publisher, except for noncommercial, educational use including classroom teaching purposes. Product or company names used in this journal are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. The views expressed in this journal are those of the authors but not necessarily of IGI Global.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Noisy images edge detection: Ant colony optimization algorithm

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

متن کامل

Image Edge Detection based on ACO-PSO Algorithm

This survey focuses on the problem of parameters selection in image edge detection by ant colony optimization (ACO) algorithm. By introducing particle swarm optimization (PSO) algorithm to optimize parameters in ACO algorithm, the fitness function based on connectivity of image edge is proposed to evaluate the quality of parameters in ACO algorithm. And the ACO-PSO algorithm is applied to image...

متن کامل

Image Edge Detection Using Quantum Ant Colony Optimization

Ant colony optimization algorithm (ACO) which performs well in discrete optimization has already been used widely and successfully in digital image processing. Slow convergence, however, is an obvious drawback of the traditional ACO. A quantum ant colony algorithm (QACO), based on the concept and principles of quantum computing can overcome this defect. In this study, a QACO-based edge detectio...

متن کامل

Ant based Swarm Computing Techniques for Edge Detection of Images- A Brief Survey

-The social insect metaphor for solving diverse problems has become an emerging issue in the current years emphasizing on stochastic construction process building the solution probabilistically. Ant Colony Optimization (ACO) is an algorithm inspired by the foraging behavior of ants wherein ants deposits a volatile chemical call pheromone on the ground surface for the purpose of foraging and col...

متن کامل

Biomedical Image Edge Detection using an Ant Colony Optimization Based on Artificial Neural Networks

Ant colony optimization (ACO) is the algorithm that has inspired from natural behavior of ants life, which the ants leaved pheromone to search food on the ground. In this paper, ACO is introduced for resolving the edge detection in the biomedical image. Edge detection method based on ACO is able to create a matrix pheromone that shows information of available edge in each location of edge pixel...

متن کامل

Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics

Ant Colony Optimization (ACO) is nature inspired algorithm based on foraging behavior of ants. The algorithm is based on the fact how ants deposit pheromone while searching for food. ACO generates a pheromone matrix which gives the edge information present at each pixel position of image, formed by ants dispatched on image. The movement of ants depends on local variance of image’s intensity val...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • IJAPUC

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2016