The Automatic Tracking Study Of Cell Microtubules Target

The visual tracking technology has been a great degree of development with the increasing computing power and computer storage capacity.Nowadays visual tracking technology has been widely used in many fields such as civil and military,intelligent transportation and human-computer interaction.In the field of video surveillance,this kind of technology has been used to monitor the security status of public places such as districts,banks and parks;in intelligent transportation,this technology has been used to control traffic flow and detect vehicle abnormal behavior;in human-computer interaction,this technology has been used to achieve the real-time human-computer interaction by recognizing people in the video image with their gestures,movements and gestures,etc.In the field of visual tracking technology,there're many algorithms of target automatic tracking such as Kalman filter,Snake model,Gaussian filtering and particle filtering.And many scholars at home and abroad have applied the theoretical tracking method to various practical tracking areas.One example is medical experiments and research,and has made a lot of results.The movement of the cell micro-tubules,which plays a supporting and intracellular transporting role in cells and a guiding role in the growth of axons,was observed to determine whether the cells are normal in medicine.One important application of the research of tracking cell micro-tubules is to evaluate the effect of anticancer drugs.The traditional research method is based on manual calibration of video images under fluorescent microscope,which requires high labor costs and exists human error.This paper describes the basic principles of visual tracking and the main methods firstly,and compares advantages and disadvantages between main methods.And summarizes an improved particle filter tracking algorithm based on the Snake model according to the movement characteristics of cell micro-tubules.In this direction,this paper introduces the basic principle of particle filter and achievement of target tracking,summarizes the Snake model and the improved one,and improves particle filter algorithm for the movement characteristics of micro-tubules.On the basis of previous research,the main research and innovation of this paper are as follows:1?On the basis of the particle filter algorithm,the algorithm of improving the tracking target is designed to improve the tracking effect and the tracking precision for the motion and distribution characteristics.Because the model of nerve micro-filament is simple and has similarity with the cell micro-tubules on the motor characteristics,the nerve micro-filament was used as the tracking target to complete the comparison experiment of particle filter algorithm and improved algorithm.2?The Snake model has been studied,and the Snake model and the improved algorithm have been compared and analyzed.In view of the movement characteristics of cell micro-tubules,the Snake model has been effectively improved,so that the improved model can more effectively and more quickly approach the edge of micro-tubules.3?The improved particle filter algorithm and Snake model have been effectively merged,so that the fusion algorithm can effectively track the cell micro-tubule target.Based on the simulation experiment,the data were collected and analyzed to determine the robustness of the experimental results,compared with the manual calibration's situation.