Constrained Hough transforms for curve detection
Computer Vision and Image Understanding
From Natural to Artificial Swarm Intelligence
From Natural to Artificial Swarm Intelligence
Point-to-line mappings as Hough transforms
Pattern Recognition Letters
Accuracy of the straight line Hough transform: the non-voting approach
Computer Vision and Image Understanding
Interaction of Color
Text feature selection using ant colony optimization
Expert Systems with Applications: An International Journal
A multi-objective ant colony system algorithm for flow shop scheduling problem
Expert Systems with Applications: An International Journal
Statistical performance analysis of track initiation techniques
IEEE Transactions on Signal Processing
Acoustic Multitarget Tracking Using Direction-of-Arrival Batches
IEEE Transactions on Signal Processing
A Consistent Metric for Performance Evaluation of Multi-Object Filters
IEEE Transactions on Signal Processing - Part I
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Hi-index | 12.05 |
Inspired from various colors of ants in organized insect communities, we propose a novel ant system with a ''subtractive'' color mixing model of three primary colors for jointly estimating the number of tracks to be initiated and their individual tracks in the multi-sensor multi-target system. Firstly, each ant is assumed to deposit only one type of colored pheromones all the time, namely, cyan, magenta, or yellow, and ant's decision depends on the colored pheromone similarity comparison with candidates to be visited. Then a mixture optimization function on a three-dimensional parameter space is proposed to exploit best solutions by the following ants, which results in a group of nearly cyan, magenta, or yellow tracks of interest. Finally, a new track initiation evaluation metric, i.e., Optimal Sub-Pattern Assignment (OSPA) distance, is introduced for the unknown number of tracks. Simulation results indicate favorable performance both in clutter-free and cluttered environment.