Ir / Visible Light Tracking Algorithm And Realization

Image tracker is the core component of image guiding system. Traditional image tracker uses CCD as signal sensor, but normally CCD can't work at night or can't "see" the targets obscured by smoke. Modern advanced image tracker which uses infrared image device can overcome these weaknesses, so the applications of image tracker are greatly expanded. For CCD and infrared imaging sensor used in image tracker, the all-weather working capability of the system has been effectively improved. Additionally early image tracker usually works in a single work model with simple tracking algorithm, so it can only work under certain conditions; even more the tracking effects are greatly different in various environments of application. With the rapid development of photoelectric convector and high-speed real-time image processing technology, image tracker inclines to multi-mode way. In this dissertation traditional correlation and contrast tracking algorithms are modified, and a dual-mode tracking algorithm combined by these two models is designed. The accuracy and stability of image tracker, which can work in complex environments, are effectively improved.The dissertation comes from the research on project XX infrared image tracker of South-West Technology and Physics Institute. Based on high-performance hardware platform of DSP (ADSP-TS201) + FPGA (The EP1S40F1020 of Stratix) and structural design of software, the image tracker realizes real-time, high-precision and high-stability image tracking. After summarizing the modern situation of research at home and abroad, then debugging DSP, the functions of this image tracker comes true finally. The main points are listed below:1.The image processing algorithm is designed to strengthen tracking effects according to the characteristics of CCD and infrared digital image signals.2.The traditional correlation tracking algorithm is modified, then a template column-changing algorithm by and correlation targets extraction algorithm based on connecting areas are designed. These strategies overcome the tracking points drifting of correlation tracking.3.Centroid tracking algorithm based on contrast is modified, and judgment methods of objectives'polarities, as well as extraction and judgment methods of several contrast targets, are designed.4.Dual-mode tracking algorithm is designed and realized: correlation tracking and centroid tracking algorithms are combined to obtain optimal tracking effects. The image tracker which uses dual-mode tracking algorithm can choose tracking algorithms smartly according to the information of targets, so the performances of the image tracker are greatly improved.