Abstract
This paper describes a contour extraction scheme which refines a roughly estimated initial contour to outline a precise object boundary. In our approach, mixture density descriptions, which are parametric descriptions of decomposed sub-regions, are obtained from region clustering. Using these descriptions, likelihoods that a pixel belongs to the object and its background are evaluated. Unlike other active contour extraction schemes, region-and edge-based estimation schemes are integrated into an energy minimization process using log-likelihood functions based on the mixture density descriptions. Owing to the integration, the active contour locates itself precisely to the object boundary for complex background images. Moreover, C1 discontinuity of the contour is realized as changes of the object sub-regions' boundaries. The experiments show these advantages.
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© 1992 Springer-Verlag Berlin Heidelberg
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Etoh, M., Shirai, Y., Asada, M. (1992). Contour extraction by mixture density description obtained from region clustering. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_3
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DOI: https://doi.org/10.1007/3-540-55426-2_3
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