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.

As the information society becomes increasingly flooded with digital images, the need for efficient image retrieval systems increases as well. To handle the vast amounts of data involved, the indexing process needs to be run automatically, using content-based descriptors extracted directly from the digital image, such as colour composition, shape and texture features. These content-based image retrieval systems are often slow and cumbersome, and can appear confusing to an ordinary user who does not understand the underlying mechanisms. One step towards more efficient and user-friendly retrieval systems might be to adjust the weight placed on various descriptors depending on which image category is being searched for. The results of this thesis show that certain categories of digital images would benefit from having extra weight assigned to colour, texture or shape features when searching for images of that category..

This essay is a survey of thirteen user studies performed in the field of image retrieval. The purpose is to try to distinguish principles that should be kept in mind when wanting to make image databases available for a wide and varied group of users. The essay tries to answer two questions, namely: Are there any results in accordance among the different studies? What in the user studies should be considered when it comes to how content description, interface and functions for searching can be designed when creating systems for image retrieval? Each study is first reviewed on its own, and then a comparative analysis of all the studies is carried out. Derived from the result of this analysis, the conclusion is presented in the form of a row of suggestions to which aspects are to be suitably included in the design of image databases.

The aim of this master ´s thesis is to understand why there are difficulties in finding joint methods and standards in the field of image indexing. The main focus for interpreting these issues is on Sara Shatford ´s article Analyzing the Subject of a Picture: A Theoretical Approach. In the article Shatford discusses a theoretical basis for identifying and classifying the subject in a picture. In doing so she uses concepts taken from The Philosophy of Art, Meaning in Language and Visual Perception. With the aid of S.R.