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Low Level Moving-Feature Extraction Via Heat Flow Analogy

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Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4291))

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Abstract

In this paper, an intelligent and automatic moving object edge detection algorithm is proposed, based on heat flow analogy. This algorithm starts with anisotropic heat diffusion in the spatial domain to remove noise and sharpen region boundaries for the purpose of obtaining high quality edge data. Then, isotropic heat diffusion is applied in the temporal domain to calculate the total amount of heat flow. The moving edges are represented as the total amount of heat flow out from the reference frame. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain binary moving edges. Evaluation results indicate that this approach has advantages in handling noise in the temporal domain because of the averaging inherent of isotropic heat flow. Results also show that this technique can detect moving edges in image sequences.

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© 2006 Springer-Verlag Berlin Heidelberg

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Direkoğlu, C., Nixon, M.S. (2006). Low Level Moving-Feature Extraction Via Heat Flow Analogy. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_25

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  • DOI: https://doi.org/10.1007/11919476_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48628-2

  • Online ISBN: 978-3-540-48631-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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