Abstract
We have developed a robust statistical edge detection method by combining the ideas of Kundus method, in which the region segmentation of local area is used, and Fukuis method, in which a statistic evaluation value separability is used for edge extraction and also have developed a region segmentation method based on the global features like the statistics of the region. A new region segmentation method is developed by combining these two methods, in which the edge extraction method is used instead of the first step of region segmentation method. We obtained the almost same results as the ones of previous region segmentation method. The proposed one has some advantages because we are able to introduce a new conspicuity degree including a clear contrast value with the adjacent regions, a envelopment degree based on clear edge and so on without much difficulty and it will contribute to develop a further unification algorithm and a new feature extraction method for scene recognition.
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Mori, F., Mori, T. (2013). Region Segmentation and Object Extraction Based on Virtual Edge and Global Features. In: Park, JI., Kim, J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer Science, vol 7728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37410-4_16
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DOI: https://doi.org/10.1007/978-3-642-37410-4_16
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