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Edge detection of Malaria parasites using ant colony optimization
- Source :
- 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC).
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- Ant colony optimization (ACO) is algorithm used for optimization motivated by the natural behaviour of species of ants. In this ants retain pheromone for foraging at the ground. ACO has been originated to detect the edges of microscopic images of blood samples which are affected by malaria disease. The edge detection approach of ACO is used to maintain pheromone matrix which determines the information of edges provided at every image pixel position, based on no. of ants movement that are dispatched to be in motion on the image. Thus, changes in the intensity values of images determine the movement of the ants. The results have been taken to study an approach for Ant Colony Edge Detection method.
- Subjects :
- Computer science
business.industry
Ant colony optimization algorithms
030231 tropical medicine
Foraging
Pattern recognition
Ant colony
01 natural sciences
Edge detection
010309 optics
03 medical and health sciences
0302 clinical medicine
0103 physical sciences
Pheromone
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)
- Accession number :
- edsair.doi...........eb6e183db08749c2768b30de5fddec18