The Laser Doppler Vibrometer (LDV)-based Acoustic to Seismic (A/S) landmine detection system is one of the reliable and powerful landmine detection techniques. The interpretation of LDV-based A/S data is performed off-line, manually, depending heavily on the skills, experience, alertness and consistency of a trained operator. This takes a long time. The manually obtained results suffer from errors, particularly when dealing with large volumes of data. This paper proposes some techniques for the automatic detection of objects from the acoustic images which are obtained from the LDV-based A/S landmine detection system. These techniques are based on color image transformations, morphological image processing and the wavelet transform. The results obtained are optimized to select the best image type and the best morphological operation used in terms of the higher probability of detection, the lower false alarm rate, the accuracy and the processing speed.
2. Kasban, H., O. Zahran, S. M. S. Elaraby, M. El-Kordy, and F. E. Abd El-Samie, "Automatic object detection from acoustic to seismic landmines images," IEEE International Conference on Computer Engineering & Systems, Cairo, Egypt, November 2008.
3. Bellman, F., A. Bulletti, and L. Capineri, "Technology survey nonlinear acoustic landmine detection study," EUDEM 2 Technology Survey Report, Lausanne, Switzerland, November, 2004.
4. Xiang, N. and J. M. Sabatier, "Landmine detection measurements using acoustic-to-seismic coupling," Proceedings of SPIE, Vol. 4038, 645-655, Orlando, USA, 2000.
5. Bradley, M. and J. M. Sabatier, "Fusion of acoustic/seismic and ground penetrating radar sensors for antitank mine detection," Proc. SPIE, Vol. 4394, 979-990, 2002.
6. Bednarz, T. P., C. Lei, and J. C. Patterson, "Particle image thermometry for natural convection flows," 16th Australasian Fluid Mechanics Conference Crown Plaza, Gold Coast, Australia, December 2007.
7. Rasras, R. J., I. M. M. El Emary, and D. E. Skopin, "Developing a new color model for image analysis and processing," COMSIS, Vol. 4, No. 1, 43-56, June 2007.
8. Kasban, H., O. Zahran, S. M. S. Elaraby, M. El-Kordy, and F. E. Abd El-Samie, "Automatic object detection from acoustic to seismic landmines images," IEEE International Conference on Computer Engineering & Systems, Cairo, Egypt, November 2008.
9. Kasban, H. Detection of buried objects using acoustic waves, M.Sc. thesis, Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia U.
10. Paik, J., C. P. Lee, and M. A. Abidi, "Image processing based mine detection techniques: A review," Subsurface Sensing Technologies and Applications: An International Journal, Vol. 3, No. 3, 153-202, July 2002. http://imaging.utk.edu/publications/papers/20-02/paik ssta02.pdf.
11. Ederra, G. B., "Mathematical morphology techniques applied to anti-personnel mine detection,", M.Sc. thesis, Vrije Universiteit Brussel (VUB), Faculteit Toegepaste Wetenschappen, ETRO Department, 1999. http://gershwin.ens.fr/great/master Basterra-1999.pdf .
12. Banerji, A. and J. Goutsias, "A morphological approach to automatic mine detection problems," Aerospace and Electronic Systems, IEEE Transactions, Vol. 34, No. 4, 1085-1096, 1998.
13. Kaiser, G., A Friendly Guide to Wavelets, Birkhauser, Boston, 1994.
14. Kasban, H., Zahran, S. M. S. Elaraby, M. El-Kordy, and F.E.Abd El-Samie, "Data interpretation of acoustic to seismic based LDV landmine detection system using morphology and wavelet," Proceeding of the International Workshop on Acoustics and Vibration in Egypt, Cairo, Egypt, Oct. 2008.