Abstract
Motion detection is the first important step in large applications of computer vision. Motion detection extracts moving objects from the background. There are many methods to do that. However, in most methods, if the input video has noise and light change, moving objects will not be extracted accurately. In this paper, we propose the method for motion detection which extracts moving objects from the background based on the image intensity ratio concept that is not affected by light change; therefore, the sensitivity with light change is overcome. The image intensity ratio is computed by the average intensity of current frame and the intensity of every pixel in that frame. The intensity ratio of a pixel is nearly unchanged between two frames. We apply the Lucas-Kanade optical flow method based on that image intensity ratio. Our proposed algorithm has good noise tolerance and is not affected by light change. For demonstrating the superiority of the proposed method, we have compared the results with the other recent methods available in literature.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Quoc, P.B., Binh, N.T. (2015). Motion Detection Based on Image Intensity Ratio. In: Vinh, P., Vassev, E., Hinchey, M. (eds) Nature of Computation and Communication. ICTCC 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-319-15392-6_33
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DOI: https://doi.org/10.1007/978-3-319-15392-6_33
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