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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abdou, I.E., Pratt, W.K.: Qualitative design and evaluation of enhancement/thresholding edge detector. Proceedings of IEEE 67(5), 753–763 (1979)
Cheikh, F.A., Gabbouj, M.: Directional unsharp masking-based approach for color image enhancement. In: Proceedings of the Noblesse Workshop on non-linear model based image analysis (NMBIA), Glasgow, UK, July 1-3, pp. 173–178 (1998)
Cheikh, F.A., Gabbouj, M.: Directional-rational approach for color image enhancement. In: Proceedings of the IEEE International Symposium on Circuits and Systems, Geneva, Switzerland, May 28–31 (2000)
Fotopoulos, S., Sindoukas, D., Laskaris, N., Economou, G.: Image enhancement using color and spatial information. IEEE International conference on Acoustics, Speech, and Signal Processing 4, 2581–2584 (1997)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley publishing company, Reading (1993)
Klette, R., Zamperoni, P.: Handbook of Image Processing Operators. John Wiley and Sons, Chichester (1996) (Extreme value sharpening and LAS)
Krug, K.D., Stein, J.A.: Advanced dual energy x-ray for explosives detection. In: Proc. of 1st International Symposium on Explosive Detection Technology, pp. 282–284 (1991)
Michette, A.G., Buckley, C.J.: X-ray science and technology, pp. 1–44. Institute of Physics Publishing, Bristol (1993)
Polesel, A., Ramponi, G., Mathews, V.J.: Image enhancement via adaptive unsharp masking. IEEE Transactions on Image Processing 9(3) (2000)
Ramponi, G.: Contrast enhancement in images via the Product of Linear filters. Signal Processing 77(3), 349–353 (1999)
Ramponi, G.: A cubic unsharp masking technique for contrast enhancement. Signal Processing 67(2), 211–222 (1998)
Rangayyan, M.R., et al.: Improvement of sensitivity of breast cancer diagnosis with adaptive neighbourhood enhancement of mammograms. IEEE Transactions on IT in Biomedicine 1(3), 161–169 (1997)
Sindoukas, D., Laskaris, N., Fotopoulos, S.: Algorithms for color image edge enhancement using potential functions. IEEE Signal Processing Letters 4(9), 269–272 (1997)
Singh, S., Bovis, K.J.: Digital Mammography Segmentation. In: Suri, J., Setarehdan, S.K., Singh, S. (eds.) Advanced Algorithmic Approach to Medical Image Segmentation: State-of-the-Art Application in Cardiology, Neurology, Mammography and Pathology, pp. 440–540. Springer, Heidelberg (2001)
Singh, M.: A machine learning approach for image enhancement and segmentation for Aviation Security. PhD Thesis (2004)
Singh, S., Al-Mansoori, R.: Identification of region of interest in digital mammograms. Journal of Intelligent Systems 10(2), 183–210 (2000)
Singh, S., Singh, M.: Explosives Detection Systems (EDS) for aviation security: a review. Signal Processing 83(1), 31–55 (2003)
Zadeh, L.A.: Fuzzy logic and its applications (1965)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Singh, M., Singh, S. (2005). Image Enhancement Optimization for Hand-Luggage Screening at Airports. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_1
Download citation
DOI: https://doi.org/10.1007/11552499_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
Online ISBN: 978-3-540-31999-3
eBook Packages: Computer ScienceComputer Science (R0)