Abstract
Content based automatic image classification systems are increasingly finding usage, e.g. in large medical image databases. This paper concentrates on a grayscale radiograph annotation task which was a part of the ImageCLEF 2006. We use local features calculated around interest points, which have recently received excellent results for various image recognition and classification tasks. We propose the use of relational features, which are highly robust to illumination changes, and thus quite suitable for X-Ray images. Results with various feature and classifier settings are reported. A significant improvement in results is seen when the relative positions of the interest points are also taken into account during matching. For the given test set, our best run had a classification error rate of 16.7 %, just 0.5 % higher than the best overall submission, and therewith was ranked second in the medical automatic annotation task at the ImageCLEF 2006. The proposed method is general, can be applied to other image classification tasks and can also be extended to colour images.
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References
Gueld, M.O., Kohnen, M., Keysers, D., Schubert, H., Wein, B.B., Bredno, J., Lehmann, T.M.: Quality of DICOM header information for image categorization. In: Proc. SPIE, Medical Imaging 2002, vol. 4685, pp. 280–287 (2002)
Schulz-Mirbach, H.: Invariant features for gray scale images. In: Sagerer, G., Posch, S., Kummert, F. (eds.) 17. DAGM - Symposium “Mustererkennung”, Reihe Informatik aktuell, Bielefeld, pp. 1–14. Springer, Heidelberg (1995)
Loupias, E., Sebe, N.: Wavelet-based salient points for image retrieval (1999)
Schael, M.: Methoden zur Konstruktion invarianter Merkmale für die Texturanalyse. PhD thesis, Albert-Ludwigs-Universität, Freiburg (June 2005)
Ojala, T., Pietikäinen, M., Mäenpää, T.: Gray Scale and Rotation Invariant Texture Classification with Local Binary Patterns. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1842, pp. 404–420. Springer, Heidelberg (2000)
Setia, L., Teynor, A., Halawani, A., Burkhardt, H.: Image Classification using Cluster-Cooccurrence Matrices of Local Relational Features. In: Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval (MIR 2006), Santa Barbara, CA, USA (October 26-27, 2006)
Clough, P., Grubinger, M., Deselaers, T., Hanbury, A., Mller, H.: Overview of the ImageCLEF 2006 photographic retrieval and object annotation tasks. In: Evaluation of Multilingual and Multi-modal Information Retrieval – Seventh Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain (to appear)
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Setia, L., Teynor, A., Halawani, A., Burkhardt, H. (2007). Grayscale Radiograph Annotation Using Local Relational Features. In: Peters, C., et al. Evaluation of Multilingual and Multi-modal Information Retrieval. CLEF 2006. Lecture Notes in Computer Science, vol 4730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74999-8_79
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DOI: https://doi.org/10.1007/978-3-540-74999-8_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74998-1
Online ISBN: 978-3-540-74999-8
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