Efficient Detection of Landmines from Acoustic Images
H. Kasban ,
Osama Zahran ,
M. El-Kordy ,
Sayed M. S. Elaraby ,
El-Sayed M. El-Rabaie and
Fathi Abd El-Samie
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.