Integrating Content-Based Image Retrieval into SBIM System

In this paper we extend the Shared Biological Image Manager (SBIM) system by incorporating a content-based image retrieval (CBIR) technique using machine learning concepts. For the classification it was applied a multiclass support vector machine (SVM) schema. Given a query image, the SVM approach performs its classification and the Euclidean distance is used to compute the similarity between the query and the images in the same class. The computational experiments show satisfactory classification accuracy and suitable retrieval results. Besides, the new SBIM was validated using integration tests which show that the methods implemented attend the proposed functionalities.