Enhancement of x-ray images for cargo and pallet search using FPCNN

被引：0

作者：

Mahgoub, Ahmed G. ^{[1
]}

Ei-Sahn, Ziad A. ^{[1
]}

Abdel-Baky, Hossam-El-Deen M. ^{[1
]}

El-Badawy, El-Sayed A. ^{[1
]}

机构：

[1] Univ Alexandria, Fac Engn, Dept Elect Engn, Alexandria 21544, Egypt

来源：

WMSCI 2007 : 11TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL V, POST CONFERENCE ISSUE, PROCEEDINGS | 2007年

关键词：

edge detection; feedback pulse coupled neural network (FPCNN); PCNN; segmentation; x-ray;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper the feedback pulse coupled neural network (FPCNN) is used for the segmentation and edge detection of x-ray images generated from American Science and Engineering (AS&E) Inc. systems used for cargo and pallet search. We prove that this technique is able to isolate important parts of x-ray images. Furthermore, our results show that the FPCNN has a good ability to retrieve small density variations which is one of the main goals of x-ray inspection.

引用

页码：131 / 135

页数：5