Learning to Classify Texture Objects by Particle Swarm Optimization Algorithm

Ye Zhiwei, Chen Hongwei, Liu Wei, Wang Chunzhi, Lai Xudong
2013 Research Journal of Applied Sciences Engineering and Technology  
Texture is an important visual attribute used to describe images. There are many methods available for texture analysis. However, most of these methods are object to variant rotation and changing scale of the images. Hence, this study presents a novel approach for texture analysis. The approach applies the Particle Swarm Optimization Algorithm in learning the texture filters for texture classifications. In this approach, the texture filter is regarded as the particle; the population of particle
more » ... ulation of particle is iteratively evaluated according to a statistical performance index corresponding to object classification ability and evolves into the optimal filter using the evolution principles of Particle Swarm Optimization Algorithm. The method has been validated on aerial images and results indicate that proposed method is feasible for texture analysis.
doi:10.19026/rjaset.5.5052 fatcat:zy3ssi6hjre7zn7kskmkk7wfru