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Region of Interest Based Image Categorization

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Data Warehousing and Knowledge Discovery (DaWaK 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6263))

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Abstract

Region Of Interest Based Image Classification (ROIBIC) is a mechanism for categorising images according to some specific component or object that features across a given image set. This paper describes and compares two such approaches. The first is founded on a weighted graph mining technique whereby the ROI is represented using a tree structure which allows the application of a weighted graph mining technique to identify features of interest, which can then be used as the foundation with which to build a classifier. The second approach is founded on a time series analysis technique whereby the ROI are represented as time series which can then be used as the foundation for a Case Based Reasoner. The presented evaluation focuses on MRI brain scan data where the classification is focused on the corpus callosum, a distinctive region in MRI brain scan data. Two scenarios are considered: distinguishing between musicians and non-musicians and epilepsy patient screening.

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Elsayed, A., Coenen, F., García-Fiñana, M., Sluming, V. (2010). Region of Interest Based Image Categorization. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2010. Lecture Notes in Computer Science, vol 6263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15105-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-15105-7_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15104-0

  • Online ISBN: 978-3-642-15105-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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