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The effects of evaluation and rotation on descriptors and similarity measures for a single class of image objects

“A picture is worth a thousand words”. If this proverb were taken literally we all know that every person interprets images or photos differently in terms of its content. This is due to the semantics contained in these images. Content-based image retrieval has become a vast area of research in order to successfully describe and retrieve images according to the content. In military applications, intelligence images such as those obtained by the defence intelligence group are taken (mostly on film), developed and then manually annotated thereafter. These photos are then stored in a filing system according to certain attributes such as the location, content etc. To retrieve these images at a later stage might take days or even weeks to locate. Thus, the need for a digital annotation system has arisen. The images of the military contain various military vehicles and buildings that need to be detected, described and stored in a database. For our research we want to look at the effects that the rotation and elevation angle of an object in an image has on the retrieval performance. We chose model cars in order to be able to control the environment the photos were taken in such as the background, lighting, distance between the objects, and the camera etc. There are also a wide variety of shapes and colours of these models to obtain and work with. We look at the MPEG-7 descriptor schemes that are recommended by the MPEG group for video and image retrieval as well as implement three of them. For the military it could be required that when the defence intelligence group is in the field, that the images be directly transmitted via satellite to the headquarters. We have therefore included the JPEG2000 standard which gives a compression performance increase of 20% over the original JPEG standard. It is also capable to transmit images wirelessly as well as securely. Including the MPEG-7 descriptors that we have implemented, we have also implemented the fuzzy histogram and colour correlogram descriptors. For our experimentation we implemented a series of experiments in order to determine the effects that rotation and elevation has on our model vehicle images. Observations are made when each vehicle is considered separately and when the vehicles are described and combined into a single database. After the experiments are done we look at the descriptors and determine which adjustments could be made in order to improve the retrieval performance thereof. / Dr. W.A. Clarke

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:9199
Date06 June 2008
Source SetsSouth African National ETD Portal
Detected LanguageEnglish
TypeThesis

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