Title :
A united classification system of X-ray image based on fuzzy rule and neural networks
Author :
Liu, Dongmei ; Wang, Zhaoxia
Author_Institution :
Dept. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
The detection of explosives in passengers¿ luggage is an important area in public traffic security. This paper presents a united classification system for detecting explosives based on fuzzy rule and neural networks. Due to imaging and influence of outer environment, preprocessing is firstly needed to improve the quality of X-ray images. Then, a test pattern may be considered as several possible objects with different degrees through the multi-level fuzzy classifier. Finally, the result of multi-level fuzzy classifier will be reconsidered through the parallel neural networks classifier. From the experience results, the united classification system performs well.
Keywords :
X-ray imaging; explosives; fuzzy set theory; image classification; national security; neural nets; object detection; public administration; X-ray image; explosives detection; fuzzy rule; multilevel fuzzy classifier; neural networks; passenger luggage; public traffic security; united classification system; Computer science; Explosives; Fuzzy neural networks; Fuzzy systems; Image classification; Image segmentation; Intelligent systems; Knowledge engineering; Neural networks; X-ray imaging;
Conference_Titel :
Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-2196-1
Electronic_ISBN :
978-1-4244-2197-8
DOI :
10.1109/ISKE.2008.4731024
