AN IMPROVED GAIT RECOGNITION SYSTEM BASED ON PCA AND ACO ALGORITHM

Manuj Mishra

Abstract


In this paper, an improved Gait recognition system using ant colony optimization algorithm and PCA algorithm is proposed. This system works on two different phases, named as Extraction phase and Recognition phase. In the extraction phase, sub-window extraction algorithm is applied on different Gait images collected from different sources. Then applied ant colony optimization algorithm to reduce number of sub windows, taken from sub window extraction algorithm. This proposed work helps to improve the overhead problem of PCA algorithm. Experiments are carried out on different datasets, collected from CASIA dataset which is in the form of silhouette images. Experimental results show that proposed work efficiency, in terms of recognition rate, is better than original PCA algorithm by reducing number of sub-windows.

Keywords- Ant colony optimization, ACO, Sub-window extraction, PCA algorithm, PCA, Gait Recognition.


Full Text:

PDF

Refbacks

  • There are currently no refbacks.


© 2017 International Journal of Global Research in Computer Science (JGRCS)
Copyright Agreement & Authorship Responsibility