Abstract
The MPEG-4 and MPEG-7 visual standard to support each frame of a video sequence should be segmented in terms of video object planes (VOPs). This paper presents an image segmentation method for extracting video objects from image sequences. The method is based on a multiresolution application of wavelet and watershed transformations, followed by a wavelet coefficient-based region merging procedure. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transformation. Second, image segmentation is used to segment the lowest-resolution image of the created pyramid by watershed transformation. Third, region merging involves merging segmented regions using the third-order moment values of the wavelet coefficients. Finally, the region projection is used to recover a full-resolution image using an inverse wavelet transformation. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as the reduction of over-segmentation.
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Kim, JB., Kim, HJ. (2002). Efficient Image Segmentation Based on Wavelet and Watersheds for Video Objects Extraction. In: Hendtlass, T., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2002. Lecture Notes in Computer Science(), vol 2358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48035-8_8
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DOI: https://doi.org/10.1007/3-540-48035-8_8
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