Abstract
We present a CBIR system (Content-based Image Retrieval). The system establishes a set of visual features which will be automatically generated. The sort of features is diverse and they are related to various concepts. After visual features calculation, a calibration process is performed whereby the system estimates the best weight for each feature. It uses a calibration algorithm (an iterative process) and a set of experiments, and the result is the influence of each feature in the main function that is used for the retrieval process. In image validation, the modifications to the main function are verified so as to ensure that the new function is better than the preceding one. Finally, the image retrieval process is performed according to the ImageCLEFmed rules, fully described in [2, 5]. The retrieval results have not been the expected ones, but they are a good starting for the future.
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Delgado, J.L., Rodrigo, C., León, G. (2009). Experiments in Calibration and Validation for Medical Content-Based Images Retrieval. In: Peters, C., et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_92
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DOI: https://doi.org/10.1007/978-3-642-04447-2_92
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