Abstract
Fast image segmentation algorithm is discussed, where first significant points for segmentation are determined. Reduced set of image points is then used in K-means clustering algorithm for image segmentation. Our method reduces segmentation of the whole image to segmentation of significant points. Reduction of points of interest is made by introducing some kind of intelligence in decision step before clustering algorithm. It is numerically less complex and suitable for implementation in the low speed computing devices, such as smart cameras for the traffic surveillance systems. Multiscale edge detection and segmentation are discussed in detail in the paper.
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Romih, T., Planinšič, P. (2008). Fast Image Segmentation Algorithm Using Wavelet Transform. In: Tsihrintzis, G.A., Virvou, M., Howlett, R.J., Jain, L.C. (eds) New Directions in Intelligent Interactive Multimedia. Studies in Computational Intelligence, vol 142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68127-4_12
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DOI: https://doi.org/10.1007/978-3-540-68127-4_12
Publisher Name: Springer, Berlin, Heidelberg
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