Object classification in images for Epo doping control based on fuzzy decision trees

Ivan Bajla; Igor Hollander; Dorothea Heiss; Reinhard Granec; Markus Minichmayr

doi:10.1117/12.585255

23 February 2005 Object classification in images for Epo doping control based on fuzzy decision trees

Ivan Bajla, Igor Hollander, Dorothea Heiss, Reinhard Granec, Markus Minichmayr

Proceedings Volume 5673, Applications of Neural Networks and Machine Learning in Image Processing IX; (2005) https://doi.org/10.1117/12.585255
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

Erythropoietin (Epo) is a hormone which can be misused as a doping substance. Its detection involves analysis of images containing specific objects (bands), whose position and intensity are critical for doping positivity. Within a research project of the World Anti-Doping Agency (WADA) we are implementing the GASepo software that should serve for Epo testing in doping control laboratories world-wide. For identification of the bands we have developed a segmentation procedure based on a sequence of filters and edge detectors. Whereas all true bands are properly segmented, the procedure generates a relatively high number of false positives (artefacts). To separate these artefacts we suggested a post-segmentation supervised classification using real-valued geometrical measures of objects. The method is based on the ID3 (Ross Quinlan's) rule generation method, where fuzzy representation is used for linking the linguistic terms to quantitative data. The fuzzy modification of the ID3 method provides a framework that generates fuzzy decision trees, as well as fuzzy sets for input data. Using the MLT^TM software (Machine Learning Framework) we have generated a set of fuzzy rules explicitly describing bands and artefacts. The method eliminated most of the artefacts. The contribution includes a comparison of the obtained misclassification errors to the errors produced by some other statistical classification methods.

Citation Download Citation

Ivan Bajla, Igor Hollander, Dorothea Heiss, Reinhard Granec, and Markus Minichmayr "Object classification in images for Epo doping control based on fuzzy decision trees", Proc. SPIE 5673, Applications of Neural Networks and Machine Learning in Image Processing IX, (23 February 2005); https://doi.org/10.1117/12.585255

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