The Study On Optical Flow Of Color Image

This thesis is the project supported by Aeronautical Foundation Science ( No.99F53065) and Research Center of Measuring and Testing Technologies, and Control Engineering in Nanchang Institute of Aeronautical Technology (No.2001-15).The motion information obtained from a sequence of time-varying two-dimensional images gives fundamental clues about the three-dimensional structure of the observed scene. For many vision systems, the main task is to extract the information.The computation of optical flow is an essential problem for the major research area of time-varying images sequence. The development and application of optical flow have been introduced in the brief. We introduced the definition, the theory and the computing method of optical flow.In traditional methods, the velocity is determined according to the assumption that the brightness of a given point equal to the brightness of the unique corresponding point in the next frame. Gradient-based techniques have been relatively successful at computing optical flow field for grey-scale images when additional constraints are added. The fundamental formula of gradient-based techniques is the so-called optical flow constraint equation, which explores the linear relationship between the intensity gradients and the optical flow components. Since this provides only one equation with two unknowns, additional constraints have to be employed to compute optical flow field. One popular approach is to add smoothness constraints while computing optical flow. Similarly, the use of color images for motion estimation is investigated by using different sets of color-related, locally computable motion "invariance". This approach is to use color images to obtain three optical flow constraint equations corresponding to three-colors components. This gives us an over-determined linear system with three equations and two unknowns which can be solved using linear least-squares algorithm. No additional constraints are necessarily needed to compute the optical flow. Based on the theories mentioned above, a new algorithm is presented to compute the acceleration in the color time-varying images. The experiments were carried out in two stages: The first step, the picture is divided into three images according to RGB model. Then, the optical flow is obtained by applying the algorithms. The second one consisted of a qualitative analysis of the results of the motion field estimation process for a known motion field. In this step, the relative errors of computation are discussed.A new experimental method is presented and different scenes have been used to verify the algorithm of the acceleration flow. The velocity and acceleration of the moving object is showed with a needle diagram.