Research On Dynamic Target Stable Tracking Technology Of Photoelectric Imaging

In the task of photoelectric image tracking, different kinds of targets exhibitdiversity of characteristics. Even the same target, it represents different characteristicsin different tracking phase or background. With the distance increasing between thetarget and the tracking system, the target imaging will exhibit extended target, masstarget and small target successively. The characteristics of the target may enduresudden variation due to asymmetric illumination, splitting and flameout in the courseof the tracking. These dynamic and diverse characteristics of the target influence theadaptabilities of the tracking algorithms and introduce instability into the trackingsystem severely.For tracking the target with changing characteristics stably, the robustsingle-mode detection and tracking algorithm for special kind of target wereresearched. For the problem of stable tracking point extraction for infrared extendedtarget, a novel approach is proposed to reduce the tracking jitter. A new contoursmoothing method based on the chord-arc ratio filtering is introduced to obtain apreliminary extraction point with lower jitters. Then a novel fine tracking pointextraction method based on the minimal inscribed circle is presented. The targetextraction based on the contrast segmentation method is used for the target tracking inthe simple background. For target stable tracking in the complex background, a noveladaptive template update method is proposed which is based on the binary templatedialation and weighting updation. A method based on the gray mophology and highpass filtering for detection small target is presented. Through the trajectory associationbased on the multi-feature and the method for extracting the centroid with backgroundremoved, the stability of the small target tracking is improved.Due to the single-mode algorithm can not suit all the variation situations of thetarget and it is difficult to track the target in all the stages, the coarse-fine paralleltracking frame is proposed to improve the tracking stability and reliability. Themulti-target coarse tracking is realized based on the multi-algorithm parallel methodin the whole view of the sight. For main target stable tracking in different phase anddifferent backgound, the double-mode tracking method based on the contrast and correlation is used. Then the capability of the system for stable tracking and theadaptability for variation of the target characteristics is improved. At last, anintelligent and robust system for auto target detection and tracking is realized.The method for target trajectory event auto recognition based on themulti-feature fuzzy fusion technology is researched, and the robust detection for somerepresentative target trajectory event and its occurrence time is realized. It can helpthe system to make decision, situation reasoning and make fast evaluation. So itimproves the intelligence and the value of the system.In order to improve the real-time performance of the system, reduce its dynamicdelay and ensure its process bandwith, the characteristics which should be included inan efficient hardware platform were discussed, based on the analyse for the featuresof the image process algorithms. The method for mapping the coarse-fine paralleltracking software onto the parallel hardware platform and the method for optimizingthe embeded software is researched. It concludes that the software must be optimizedbased on both algorithm level and code level for achieving real-time performance fora given hardware platform. Through efficient software optimization, the real-timeperformance of the image-based system is improved and the stable tracking isrealized.