Underwater object identification has been of great interest for a few years to acousticians (detection of boulders), marines (detection of buried mines), or archaeologists (detection of wreckage). Image and signal processing succeed in identifying objects lying on the sea bottom, however identification of an object buried in sediment remains complex. The purpose of this work is to develop a complete identification of objects embedded in the sediment using an adapted technology. We use a parametric source, whose properties are based on the nonlinear propagation characteristics of the water; it has many advantages as an acoustic source (high relative bandwidth, narrow beam) which are useful for object detection and classification. This paper presents two algorithms: the first one improves the object detection and the second procedure computes discriminant parameters from images to classify these objects.
['David Boulinguez', 'André Quinquis']
Underwater buried object recognition using wavelet packets and Fourier descriptors