A Novel Modified SFTA Approach for Feature Extraction

被引：0

作者：

Hasan, Md. Junayed ^{[1
]}

Uddin, Jia ^{[1
]}

Pinku, Subroto Nag ^{[1
]}

机构：

[1] BRAC Univ, Dept Comp Sci & Engn, Dhaka 1212, Bangladesh

来源：

2016 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATION & COMMUNICATION TECHNOLOGY (ICEEICT) | 2016年

关键词：

SFTA (Segmentation Based Fractal Texture Analysis); multilevel thresholing; HGAPSO; Otsu function;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：5

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