Author(s)

Donghua Gu¹, Zhenyu Han¹, Qing’e Wu^2*

¹Engineering Training Center, Zhengzhou University of Light Industry, Zhengzhou, China.
²School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.

In order to let machine better imitate thinking method of people to perform recognition and classification for fuzzy and uncertain thing, this paper puts forward a fuzzy and rough association method to deal with the problem. However, the application of fuzzy rough sets (FRS) will be introduced mainly on pattern recognition. Some related theories on FRS would be discussed, and some fuzzy rough mathematical methods on pattern-recognition will be given. Then, concrete applications of FRS on image processing and recognition will be introduced. Simulation result signifies that this fuzzy and rough association method is not only fast but also closer to nature attribute of thing for processing and recognizing image by comparing with the single neural network and other recognition device. The recognition rate is about 95.78%.

FR Proximity, Maximum Principle of Membership, Principle of Proximity, Target Recognition

Gu, D. , Han, Z. and Wu, Q. (2017) Application of FRS on Target Recognition. Open Journal of Applied Sciences, 7, 503-510. doi: 10.4236/ojapps.2017.710036.