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A DCT-Domain Approach to Image Change Detection and Its Application to Patient Video Monitoring

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3 Author(s)
Qiang Liu ; Laboratory for Computational Neuroscience, Departments of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15261, USA; Laboratory for Computational Neuroscience, Departments of Electrical Engineering, and University of Pittsburgh, Pittsburgh, PA 15261, USA. E-mail: qliu@neuronet.pitt.edu ; Robert J. Sclabassi ; Mingui Sun

Change detection is a useful tool to identify content changes in images. Its significance is found in the applications of video surveillance, editing, coding and analysis. In this work, we present another application of change detection to patient video monitoring, based on a novel approach in the discrete cosine transform (DCT) domain. This approach is built upon a statistical test on the difference between DCT-blocks, where the noise disturbances and illumination variations are excluded from the meaningful changes. Our experimental results show that the proposed method is robust in detecting content changes and may be used to facilitate high-level segmentation tasks

Published in:

2005 IEEE 7th Workshop on Multimedia Signal Processing

Date of Conference:

Oct. 30 2005-Nov. 2 2005