Study On Status Detection Of Underwater Circular Objects Based On Monocular Laser Imaging

Underwater laser imaging is widely used in ocean, river and lake exploration, which makes vision-based object localization possible. Using the mapping relationship from the3D object to the2D image, the orientation and position of the object with respect to the camera can be calculated. Localization of circular feature, which is one of the most common features, is always the research hotspot. However, very few people aimed at the localization of underwater circular features (UCFs), since image distortion and degradation occur in underwater environment. Using underwater continuous laser imaging, based on the monocular imaging model for UCFs, this thesis completes object localization by only single image of the UCFs. The main research achievements are as follows:Firstly, by the images of a cylinder object with a diameter of500mm in indoor natural lighting environment, the monocular imaging model for atmosphere circular features is checked. The distance from the object to the camera is obtained with an average relative error of2%. Based on the atmosphere vision model, the monocular imaging model for UCFs is proposed. The model compensates the image distortion by light refraction, and decomposes the object localization problem into solving the equation of the constructed cone and coordinate system transformation problem.Secondly, based on the monocular imaging model for UCFs, the algorithm of computing the orientation and center coordinates of the UCFs is given. It is based on geometric constraint, which provides a closed-form solution, and without any iteration approximation. Therefore, the result of object localization would be absolutely right as long as the image ellipse equation is absolutely accurate. This is proven by numerical simulation of the algorithm. In the meanwhile, the algorithm requires that the angle between the circular feature plane and the CCD plane is in the range of±15. The3DsMax simulation experiment prove that the error for orientation detection is less than r, and that for position detection is lower than3%.Thirdly, the accuracy of localization is directly determined by image ellipse detection. Based on traditional methods, a novel ellipse detecting algorithm constrained by edge curvature and orthogonal distance is proposed. Numerical results prove that the algorithm is not affected by iterative initial value and with good approaching rate. Synthetic image experiments prove good performance both with occluded and overlapping ellipses. No matter from the results of numerical, synthetic image or real image experiments, all prove that the ellipse detection accuracy, recall ratio, and fitting precision of the algorithm are superior to traditional methods. Moreover, the fitting result is not sensitive to the number of edge pixels, when that of traditional methods dramatically declines with more than50pixels.Fourthly, by the image degradation model of forward and backward scattering, the underwater laser image preprocessing method is studied. Homomorphic filter can eliminate multiplicative noise, when median filter is very effective to speckle noise. Combining the two kinds of filter, the quality of underwater images can be improved. Subjectively, from the results of Canny edge detection, the method reduces the influence of the noise to image edge, and effectively maintain the elliptic characteristics of the cylinder object. Objectively, both value of PSNR and NMSE prove that the method is superior to the traditional linear filter and wiener filter in both noise reduction and detail fidelity abilities.Fifthly, aimed at a water area monitoring issue, a localization system for objects with UCFs is designed. Solutions for some engineering problems, such as camera calibration, blind area of the cameras, and deformation of the mounting plate are given. Both effectiveness and localization accuracy are checked by virtual reality simulation of the system through3DsMax. At last, an experimental system is constructed in a pool with clean water to estimate the location of a cylinder object with a diameter of320mm. The accuracy and stability of the image preprocessing method, ellipse detecting method, and object localization method are thoroughly analyzed by moving and relocating the object.