面向广域监控的视频图像运动目标自动检测

1993 Proceedings of IEEE International Carnahan Conference on Security Technology Pub Date : 1993-10-13 DOI:10.1109/CCST.1993.386826

C. Munno, H. Turk, J. Wayman, J. Libert, T. Tsao

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引用次数: 12

摘要

介绍了两种用于自然场景下视频红外图像运动目标指示的图像处理技术。研究表明，视频序列的频域时空滤波和图像帧对的时空约束误差能够在低图像对比度、目标红外图像模式变化、传感器噪声或背景杂波的情况下检测和跟踪自然场景中的运动目标(如人员)。结果表明，运动滤波算法在处理被加性噪声破坏的数据序列时是有效的。实验证明了恒虚警率自适应阈值算法在控制运动检测虚警率方面的有效性。这些步骤使大量的数据减少，从而使实时处理成为可能。

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Automatic video image moving target detection for wide area surveillance

Two image processing techniques developed for moving target indication from video infrared imagery in natural scenes are presented. It is shown that frequency domain spatio-temporal filtering of video sequences and spatio-temporal constraint error of image frame pairs are able to detect and track moving targets (e.g., personnel) in natural scenes in spite of low image contrast, changes in the target's infrared image pattern, sensor noise, or background clutter. The effectiveness of the motion filtering algorithms when applied to sequences of data corrupted with additive noise is shown. The effectiveness of the CFAR (constant false alarm rate) adaptive threshold algorithm in controlling the false alarm rate for motion detection has been demonstrated. These steps have permitted substantial data reduction so that real-time processing is possible.<>

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来源期刊

1993 Proceedings of IEEE International Carnahan Conference on Security Technology

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