Automatic target detection and tracking system using infrared imagery

1997 ◽  
Author(s):  
Biao Li ◽  
Zhenkang Shen ◽  
Jicheng Li
Keyword(s):  
Target Detection ◽  
Tracking System ◽  
Infrared Imagery ◽  
Automatic Target Detection ◽  
Detection And Tracking

Target Detection and Tracking Based on Ship Borne Infrared Imagery

2010 ◽  
Vol 439-440 ◽  
pp. 546-551 ◽  
Author(s):  
Wen Hua Hu ◽  
Kai Yu Xu ◽  
Chao Jian Shi
Keyword(s):  
Target Detection ◽  
Real Life ◽  
Infrared Image ◽  
Intensity Variation ◽  
Target Position ◽  
Infrared Imagery ◽  
Automatic Target Detection ◽  
Detection And Tracking ◽  
Variation Function ◽  
Detection Mode

A novel automatic target detection and tracking algorithm for tracking targets based on ship borne infrared imagery is proposed in this paper. The algorithm has two modes: detection and tracking. In detection mode, the proposed algorithm utilized difference between the consecutive frames and top-hat filter to determine the target position. In tracking mode, the Intensity Variation Function (IVF) is utilized. Before tracking and location the new position, the algorithm should determine the IVF whether reliable. If unreliable, the mode turns to detection. Experimental results by using real-life infrared image sequence are shown to validate the robustness of the proposed technique.

The Research of Moving Target Detection and Tracking System Based on DM6437

2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei
Keyword(s):  
Target Detection ◽  
Digital Signal Processor ◽  
Moving Objects ◽  
Tracking System ◽  
Digital Signal ◽  
Gaussian Mixture ◽  
Background Model ◽  
Moving Target ◽  
Moving Target Detection ◽  
Detection And Tracking

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.

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