Classification of underwater objects using Fourier descriptors

Underwater object identification is 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 goal of this work is to propose a complete identification of objects embedded in the sediment using an adapted technology. We use a parametric source, which 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 a procedure which computes discriminant parameters from images to classify these objects