Abstract
Mining useful patterns in image databases can not only reveal useful information to users but also help the task of data management. In this paper, we propose an image mining framework, Frequent Spatial Pattern mining in images (FSP), to mine frequent patterns located in a pair of spatial locations of images. A pattern in the FSP is associated with a pair of spatial locations and refers to the occurrence of the same image content in a set of images. This framework is designed to be general so as to accept different levels of representations of image content and different layout forms of spatial representations.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chen, WT., Chen, YL., Chen, MS. (2006). Mining Frequent Spatial Patterns in Image Databases. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_80
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DOI: https://doi.org/10.1007/11731139_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33206-0
Online ISBN: 978-3-540-33207-7
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