| With the development of infrared imaging technology and digital image processing technology,infrared image processing technology has been widely used in video surveillance,target warning,infrared guidance and other military and civilian fields.Infrared moving target detection is an important application of infrared image processing,play a key role in target classification,recognition and tracking,which is of great significance.Firstly,this paper analyzes the imaging principle of infrared detectors,and according to the characteristics of the infrared image,we introduced denoising preprocessing technologys of infrared image,which improved the quality of infrared imaging and be helpful to moving target detection;Then,we classified common algorithms of moving target detection and interpretated them detailedly,and we had a close glimpse about mixed Gauss model algorithm and ViBe algorithm.In order to solve shortcomings of these algorithms and enhance the ability of resistance to complex background interference,we proposed a novel moving target detection algorithm which could adapting complex background interference,and we called the algorithm Adaptive Complex Background Segmentation(ACBS).We apply the algorithm to different scenarios for emulating,the results show that the algorithm can suppress interference from complex background and improve the accuracy of moving target detection.Finally,we designed the infrared moving target detection system based on the platform of the CPCI computer.The system is divided into four parts:infrared image acquisition module,image processing module,image display module and system control module.The image processing module is made of TMS320C6678 chip and XC7K325 chip which is the core of the system.After the hardware platform connection is completed,We debugged the platform and realized the communication of each hardware.Then we transplanted ACBS to the system platform successfully,and realized the real-time detection of infrared moving targets. |
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