DocumentCode :
1854532
Title :
Optimizing image enhancement for screening luggage at airports
Author :
Singh, Maneesha ; Singh, Sameer
Author_Institution :
Res. Sch. of Informatics, Loughborough Univ.
fYear :
2005
fDate :
March 31 2005-April 1 2005
Firstpage :
131
Lastpage :
136
Abstract :
Image enhancement is very important for increasing the sensitivity of screening luggage performance at airports. On the basis of 11 statistical measures of image viewability we propose a novel approach to optimizing the choice of image enhancement tools. We propose a neural network predictor that can be used for predicting, on a given test image, the best image enhancement algorithm for it. The network is trained using a number of image examples. The input to the neural network is a set of viewability measures and its output is the choice of enhancement algorithm for that image. On a number of test images we show that such a predictive system is highly capable in forecasting the correct choice of enhancement algorithms (as judged by human experts). We compare our predictive system against a baseline approach that uses a fixed enhancement algorithm for all batch test images, and find the proposed model to be substantially superior
Keywords :
airports; image enhancement; neural nets; security; airports; aviation security; image enhancement; image viewability; neural network predictor; screening luggage; Airports; Explosives; Humans; Image enhancement; Image quality; Informatics; Neural networks; Security; System testing; X-ray imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Homeland Security and Personal Safety, 2005. CIHSPS 2005. Proceedings of the 2005 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9176-4
Type :
conf
DOI :
10.1109/CIHSPS.2005.1500627
Filename :
1500627
Link To Document :
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