This paper aims to combine intuition and practical experience in the context of ImageCLEF 2013 Plant Identification task. We propose a flexible, modular system which allows us to analyse and combine the results after applying methods such as image retrieval using LIRe, metadata clustering and naive Bayes classification. Although the training collection is quite extensive, covering a large number of species, in order to obtain accurate results with our photo annotation algorithm we enriched our system with new images from a reliable source. As a result, we performed four runs with different configurations, and the best run was ranked 5th out of a total of 12 group participants.
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