Research On The Target Detection And Pose Estimation Method In Shallow Seawater

As the cradle of earth's species origin,the ocean occupies 70.8 percent of the earth's surface space,it is an important guarantee for the sustainable biodiversity of our planet.With the rapid growth of the world's population and the increasing scarcity of available resources in the inland,humans realize that the rich biological and mineral species in the ocean will become the guarantee of future survival resources.At present,the ocean is seriously polluted by human beings,and the amount of garbage and floating objects on the sea is increasing,which has far exceeded the purification capacity of the ocean.And because the physiological characteristics of the human body are not suitable for long-term Marine environment operations,therefore,the shallow underwater fishing equipment came into being.At present,the efficiency of salvage equipment is low and the degree of automation is not high.Therefore,this paper studies the detection and pose estimation of target based on the shallow underwater environment through computer visionFirstly,in view of the problem of water atomization caused by the scattering of light from underwater suspended material,based on the defog algorithm of land-based dark channel prior to(DCP),a background light estimation method based on the underwater environment is proposed,which combines the coefficient estimation of the dark channel and the blue and green channel with weak underwater attenuation,and realizes the restoration of the underwater image.In view of the problems of image contrast drop,color distortion and detail blur caused by the severe attenuation of light in water,the histogram equalization and Laplace sharpening are combined,and an adaptive enhancement algorithm is proposed to make the image of different environments be reasonably enhanced.At the same time,the processed image is evaluated objectively.Secondly,in view of the location offset caused by the refraction of water,based on Snell's law,an underwater binocular camera imaging model is established,a depth correction method with inherent depth as a priori is proposed,and the correction and experimental verification of the underwater position are completed.Facing with a series of problems such as low recognition rate and slow matching speed of feature point-based universal matching algorithm in underwater environment,and proposed an underwater identification code recognition algorithm applied to the surface,through optimization,the recognition speed is greatly improved,and the feasibility of the algorithm is verified by experiments.The RANSAC point cloud segmentation and ICP point cloud registration were applied to the underwater pose estimation because of the poor underwater image quality and the inability of point estimation and line estimation to meet the accuracy requirements.Finally,an evaluation standard is established by the optical motion capture system to evaluate the accuracy of the pose estimation of binocular camera.Finally,an experimental platform was built to simulate the underwater environment conditions,and the effectiveness of underwater image processing,the target detection and pose estimation is verified by experiments.The necessity and superiority of underwater image processing algorithm are verified by target detection of images processed by different algorithms based on recognition code.The feasibility and identification rate of the target detection and pose estimation algorithm are verified by outdoor the target detection and pose estimation experiments.