Infrared dim and small target detecting and tracking method inspired by Human Visual System

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• 作者：Xiabin Dong ; Xinsheng Huang ; Yongbin Zheng ; Lurong Shen ; Shengjian Bai
• 关键词：Infrared small target tracking ; Human Visual System ; DOG filter ; Gaussian window ; PID algorithm
• 刊名：Infrared Physics and Technology
• 出版年：January, 2014
• 年：2014
• 卷：62
• 期：Complete
• 页码：100-109
• 全文大小：3629 K

文摘

Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.