Research On The Image Segmentation And Object Tracking Based On The Variational Level Set Method

The variational level set method are widely used in many areas, such as the medicalimage segmentation and video tracking. However, the existing active contour models aresuitable for the intensity uniform gray images, and not suitable for the intensityinhomogeneity images and low-contrast grayscale images, which have directly limited theapplication of the active contour models. Moreover, there are some fields need to be improved,such as the calculation complexity, the sensitiveness of initial conditions, and which are easyto fall into the local minima solution.In order to improving the segmentation accuracy and reducing the segmentation time,three active contour models are proposed after the research of image segmentation algorithm,which can segment the inhomogeneity intensity images and serial images. Three kinds of theimage segmentation algorithm have achieved the good experiment results. The maintheoretical and practical results are as following:(1) In the variational level set segmention algorithms, the C-V model can not segmentthe images with inhomogeneity target and background, and the local intensity information areonly considered into the LBF model which has appeared the over segmentation phenomenon.For these problems, we have proposed the local and global binary fitting active contoursmodel, which has combined the advantage of C-V model and LBF model. Three energyfunctionals are determined, which are local energy functional, global energy functional andpunishment energy functional. Due to introduce the punishment items of level set function,we have not only eliminated the reinitialized steps, but also reduced the sensitivity of theLGBF model for initial contours. At the same time, this research has given the theory solutionof curve evolution, the numerical approximate solutions of the half implicit difference scheme,and inhomogeneity image segmentation algorithm. We have taken experiments for theinhomogeneity gray images and medical CT images, and compared with the C-V model andLBF model. It can be concluded that the LGBF model is reliable and effective.(2) In view of multiphase segmentation problem in medical image processing, the two regional LGBF model has been extended into the multiphase level set method for activecontours model, which can characterize the target areas of the given medical CT images.According to the variational level set method, the energy functional expressions for themultiphase image segmentation have been proposed in this research. The target areas of themedical CT images and MR images have obvious structure characteristic, which arecomposed of four parts, white substance area, pale gray matter area, dark grey area and blackbackground. The intensity of the four areas are not uniform. In order to classified the differenttarget areas more clearly, four-phase image segmentation has been taken as an example, andthe evolution equations of the improved model have been derived from the theory of solvingprocess. It has been designed that the half implicit difference scheme of numericalimplementation scheme with unconditional stability. We have obtained the satisfactorymultiphase segmentation results through the segmentation experiments of inhomogeneitymedical images.(3) The object detection and tracking have need to meet the requirements of real-timeand accuracy in medical video stream. The serial images of coronary artery have thecharacteristic with inhomogeneity intensity, and the target areas are closed to the backgroundareas, also the shape of target areas have changed obviously. This research work has proposeda fast single-parameter active contour model without edges, which can quickly locate thetarget position based on the geodesic active contours model. The given energy functionalexpressions of the new model have included the geodesic active region items, local binaryfitting items, the length constraint items and the symbol distance penalty items; according tothe variational level set method, the energy functionals are minimized by Euler-Lagrangeequation, and we have got the gradient descent flow equations; then determined the boundaryof moving object, extracted the background of moving object and estimated the motion vectorfield, which have adapted the topology changes of moving targets. Finally, we have done theexperiment of the serial images of coronary angiography, and the experimental results aresatisfactory.