Real-time Underwater Imaging System for Mineral Source Location and Concentration

摘要

Remote robotic exploration holds vast potential for gaining knowledge about extreme environments accessible to humans only with great difficulty.In the last two decades,various underwater devices were developed for detecting the mines and mine-like objects in the deep-sea environment.However,there are some problems in recent equipment,such as poor accuracy of mineral objects detection,without real-time processing,and low resolution of underwater images.The underwater objects recognition is a difficult task,because the physical properties of the medium,the captured images are distorted seriously by scattering,absorption and noise effects.Scattering is caused by large suspended particles,such as in turbid water,which contains abundant particles,algae,and dissolved organic compounds.Colour change corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths,rendering ambient underwater environments dominated by a bluish tone.Furthermore,in the imaging plane,there always contains noise that caused by algae or organic particulates.To solve all of these problems,in this paper,we are considering utilizing the image processing methods to determine the mineral location and to recognize the mineral actually within a little processing time.We firstly analysis the recent underwater imaging models,and propose a novel underwater optical imaging model,which is much closer to the light propagation model in the underwater environment.In our imaging system,we remove the electrical noise by dual-tree complex wavelet transform.Then,solving the non-uniform illumination of artificial lights by fast guided trilateral bilateral filter and recovering the image colour through automatic colour equalization.Finally,a shape-based mineral recognition algorithm is proposed for underwater objects detection.These methods are designed for real-time execution on limited-memory platforms,and are suitable for detecting underwater objects in practice.The Initial results are presented and experiments demonstrate the effectiveness of the proposed imaging system.