A novel modified SFTA approach for feature extraction

M. J. Hasan, J. Uddin and S. N. Pinku, "A novel modified SFTA approach for feature extraction," 2016 3rd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), Dhaka, Bangladesh, 2016, pp. 1-5, doi: 10.1109/CEEICT.2016.7873115.

Abstract

To increase the efficiency of conventional Segmentation Based Fractal Texture Analysis (SFTA), we propose a new approach on SFTA algorithm. We use an optimum multilevel thresholding hybrid method of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), called HGAPSO with the optimization technique for classification based on grey level range to get more accurate output. Experimental results show that proposed approach exhibits average 2% higher classification accuracy than conventional SFTA for our tested dataset.