Vad säger bilden? : En utvärdering av återvinningseffektiviteten i ImBrowse

Sammanfattning: The aim of this master thesis is to evaluate the performance of the content-based image retrieval system ImBrowse from a semantic point of view. Evaluation of retrieval performance is a problem in content-based image retrieval (CBIR). There are many different methods for measuring the performance of content-based image retrieval systems, but no common way for performing the evaluation. The main focus is on image retrieval regarding the extraction of the visual features in the image, from three semantic levels. The thesis tries to elucidate the semantic gap, which is the problem when the systems extraction of the visual features from the image and the user’s interpretation of that same information do not correspond. The method of this thesis is based on similar methods in evaluation studies of CBIR systems. The thesis is an evaluation of ImBrowse’s feature descriptors for 30 topics at three semantic levels and compared the descriptors performance based on our relevance assessment. For the computation of the results the precision at DCV = 20 is used. The results are presented in tables and a chart. The conclusion from this evaluation is that the retrieval effectiveness from a general point of view did not meet the semantic level of our relevance assessed topics. However, since the thesis do not have another system with the same search functions to compare with it is difficult to draw a comprehensive conclusion of the results.