2nd International ICST Conference on Mobile Multimedia Communications

Research Article

Image classification using biologically inspired systems

  • @INPROCEEDINGS{10.1145/1374296.1374326,
        author={Tomas Piatrik and Krishna Chandramouli and Ebroul Izquierdo},
        title={Image classification using biologically inspired systems},
        proceedings={2nd International ICST Conference on Mobile Multimedia Communications},
        keywords={Binary Image Cassifier; COP-K-Means; Self Organizing Feature Maps (SOFM); Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO).},
  • Tomas Piatrik
    Krishna Chandramouli
    Ebroul Izquierdo
    Year: 2006
    Image classification using biologically inspired systems
    DOI: 10.1145/1374296.1374326
Tomas Piatrik1,*, Krishna Chandramouli1,*, Ebroul Izquierdo1,*
  • 1: Queen Mary University of London, London, UK
*Contact email: tomas.piatrik@elec.qmul.ac.uk, krishna.chandramouli@elec.qmul.ac.uk, ebroul.izquierdo@elec.qmul.ac.uk


In this paper the problem of the image classification based on biologically inspired optimization systems is addressed. Recent developments in applied and heuristic optimization have been strongly influenced and inspired by natural and biological system. The findings of recent studies are showing strong evidence to the fact that some aspects of the collaborative behavior of social animals such as ants and birds can be applied to solve specific problems in science and engineering. Two algorithms based on this paradigm Ant Colony Optimization and Particle Swarm Optimization are investigated in this paper. The comparative evaluation of the recently developed techniques by the authors for optimizing the COP-K-means and the Self Organizing Feature Maps for the application of Binary Image Classification is presented. The precision and retrieval results are used as the metrics of comparison for both classifiers.