원문정보
초록
영어
With the continuous development of computer science and technology, image processing and analysis gradually form the scientific system. Although history of image processing is not long, it attracts many researchers study on it. Digital media image widely exists in many fields, such as education, video, advertisement, and so on. Process digital media image is an important part of image processing. When analyze the digital media image, we want to extract the image part we care from the original image and then method for image segmentation is quite important. That is to say that the image segmentation will divide the image into a number of regions with specific and unique nature. How to keep the original characteristics of the digital media image is quite important in the image segmentation. In this paper, we propose a new algorithm for digital media image segmentation, and it is also can be used in the image processing. The algorithm is based on asynchronous particle swarm optimization algorithm to obtain the adaptive threshold; take the inertia factor into the algorithm, the optimal threshold has been acquired for the image segmentation. Compared with other particle swarm optimization algorithm, the algorithm has the advantages of stable, easy to converge to the optimal solution, and high segmentation speed.
목차
1. Introduction
2. Several Image Segmentation Algorithms
2.1 Segmentation Method based on Region
2.2 Segmentation Method based on Edge
2.3 Image Segmentation Method Combining Edge and Region
2.4 Segmentation Method based on the Specific Theory
2.5 Two Dimensional Entropy Methods
3. The New Algorithm
3.1 PSO
3.2 Asynchronous PSO
3.3 Optimal Threshold Image Segmentation based on Asynchronous PSO
3.4 Inertia Adaptive PSO Algorithm
4. Experimental Analysis
5. Conclusions
References