DocumentCode :
677409
Title :
A novel multi-cell tracking algorithm based on ant colony behavior
Author :
Qinglan Chen ; Benlian Xu ; Mingli Lu
Author_Institution :
Changshu Inst. of Technol., Changshu, China
fYear :
2013
fDate :
25-28 Nov. 2013
Firstpage :
111
Lastpage :
115
Abstract :
This paper aims to develop a novel framework of multi-cell tracking using intelligent ant system, in which a priori colony distribution block is first proposed to directly place birth ants on relevant pixels of current image through kernel density probability estimate of background; afterwards, a multi-colony reconstruction block is developed to further attract ants towards potential regions according to heuristic histogram similarity and pixel pheromone level with an appropriate evaporation and propagation model; finally, a cell state extraction block is implemented to adaptively determine the number of cells and their individual states. Experiment results on real cell image sequences demonstrate that our algorithm could give a more accurate and robust performance than other methods.
Keywords :
ant colony optimisation; image sequences; medical image processing; object tracking; a priori colony distribution block; ant colony behavior; cell state extraction block; heuristic histogram similarity; intelligent ant system; kernel density probability; multi-colony reconstruction block; novel multicell tracking algorithm; pixel pheromone level; real cell image sequences; Adaptation models; Clustering algorithms; Heuristic algorithms; Histograms; Image reconstruction; Image sequences; Kernel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Information Sciences (ICCAIS), 2013 International Conference on
Conference_Location :
Nha Trang
Print_ISBN :
978-1-4799-0569-0
Type :
conf
DOI :
10.1109/ICCAIS.2013.6720539
Filename :
6720539
Link To Document :
بازگشت