Abstract
There have been many features developed for images, like Blob, image patches, Gabor filters, etc. But generally the calculation cost is too high. When facing a large image database, their responding speed can hardly satisfy users’ demand in real time, especially for online users. So we developed a new image feature based on a new region division method of images, and named it as ‘stripe’. As proved by the applications in ImageCLEF’s medical subtasks, stripe is much faster at the calculation speed compared with other features. And its influence to the system performance is also interesting: a little higher than the best result in ImageCLEF 2004 medical retrieval task (Mean Average Precision — MAP: 44.95% vs. 44.69%), which uses Gabor filters; and much better than Blob and low-resolution map in ImageCLEF 2006 medical annotation task (classification correctness rate: 75.5% vs. 58.5% & 75.1%).
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References
Clough, P., Müller, H., Deselaers, T., Grubinger, M., Lehmann, T., Jensen, J., Hersh, W.: The CLEF 2005 Cross-Language Image Retrieval Track. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Jones, G.J.F., McDonald, K.: Dublin City University at CLEF 2005: Experiments with the ImageCLEF St Andrew’s Collection. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Chang, Y.-C., Lin, W.-C., Chen, H.-H.: Combining Text and Image Queries at Image CLEF 2005. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Besançon, R., Millet, C.: Merging Results from Different Media: Lic2m Experiments at Image CLEF 2005. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Stehling, R.O., Nascimento, M.A., Falcao, A.X.: A compact and efficient image retrieval approach based on border/interior pixel classification. In: CIKM 2002: Proceedings of the eleventh international conference on information and knowledge management, McLean, Virginia, USA (2002)
Deselaers, T., Weyand, T., Keysers, D., Macherey, W., Ney, H.: FIRE in ImageCLEF 2005: Combining Content-based Image Retrieval with Textual Information Retrieval. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Petkova, D., Ballesteros, L.: Categorizing and Annotating Medical Images by Retrieving Terms Relevant to Visual Features. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Rahman, M.M., Desai, B.C., Bhattacharya, P.: Supervised Machine Learning based Medical Image Annotation and Retrieval. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Güld, M.O., Thies, C., Fischer, B., Lehmann, T.M.: Combining Global features for Content-based Retrieval of Medical Images. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Cheng, P.-C., Chien, B.-C., Ke, H.-R., Yang, W.-P.: NCTU_DBLAB@ ImageCLEFmed 2005: Medical Image Retrieval Task. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Müller, H., Geissbühler, A., Marty, J., Lovis, C., Ruch, P.: Using medGIFT and easyIR for the ImageCLEF 2005 Evaluation Tasks. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Qiu, B., Tian, Q., Xu, C.S.: Report on the Annotation Task in Image CLEFmed 2005. In: Cross Language Evaluation Forum 2005 Workshop, Vienna, Austria (September 2005)
Deselaers, T., Keysers, D., Ney, H.: Improving a Discriminative Approach to Object Recognition using Image Patches. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds.) DAGM 2005. LNCS, vol. 3663, pp. 326–333. Springer, Heidelberg (2005)
Maree, R., Geurts, P., Piater, J., Wehenkel, L.: Biomedical Image Classification with Random Subwindows and Decision Trees. In: ICCV 2005 workshop-CVBIA (2005)
Xiong, W., Qiu, B., Tian, Q., Xu, C., Ong, S.H., Foong, K.: Content-based Medical Retrieval Using Dynamically Optimized Regional Features. In: ICIP 2005, Genova, Italy, September 11-14 (2005)
Müller, H., Geissbühler, A., Ruch, P.: Report on the CLEF Experiment: Combining Image and Multilingual Search for Medical Image Retrieval. In: Peters, C., Gey, F.C., Gonzalo, J., Müller, H., Jones, G.J.F., Kluck, M., Magnini, B., de Rijke, M., Giampiccolo, D. (eds.) CLEF 2005. LNCS, vol. 4022, pp. 718–727. Springer, Heidelberg (2006)
Clough, P., Sanderson, M., Müller, H.: The CLEF Cross Language Image Retrieval Track (ImageCLEF) 2004. In: Heery, R., Lyon, L. (eds.) ECDL 2004. LNCS, vol. 3232, pp. 243–251. Springer, Heidelberg (2004)
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Qiu, B., Racoceanu, D., Xu, C.S., Tian, Q. (2006). Stripe: Image Feature Based on a New Grid Method and Its Application in ImageCLEF. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_37
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DOI: https://doi.org/10.1007/11880592_37
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