A knowledge-based framework for image enhancement in aviation security

Author

Singh, Maneesha ; Singh, Sameer ; Partridge, Derek

Author_Institution

Dept. of Comput. Sci., Univ. of Exeter, UK

Volume

34

Issue

6

fYear

2004

Firstpage

2354

Lastpage

2365

Abstract

The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

Keywords

X-ray imaging; avionics; image enhancement; knowledge based systems; neural nets; X-ray images; aviation security; image analysis; image enhancement; image features; image viewability; knowledge-based framework; neural networks; real images; Airports; Explosives; Helium; Humans; Image analysis; Image enhancement; Information security; Knowledge based systems; Neural networks; X-ray imaging; Aviation security; X-ray; image analysis; image viewability; knowledge-based framework; neural networks; Algorithms; Artificial Intelligence; Aviation; Expert Systems; Humans; Neural Networks (Computer); Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Security Measures; Signal Processing, Computer-Assisted; Terrorism; User-Computer Interface;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/TSMCB.2004.835077

Filename

1356024