Security methods based on biometrics have been gaining importance increasingly in the last few years due to recent advances in biometrics technology and its reliability and efficiency in real world applications. Also, several major security disasters that occurred in the last decade have given a new momentum to this research area. The successful development of biometric security applications cannot only minimise such threats but may also help in preventing them from happening on a global scale. Biometric security methods take into account humans’ unique physical or behavioural traits that help to identify them based on their intrinsic characteristics. However, there are a number of issues related to biometric security, in particular with regard to surveillance images. The first issue is related to the poor visibility of the images produced by surveillance cameras and the second issue is concerned with the effective image retrieval based on user query. This research addresses both issues. This research addresses the first issue of low quality of surveillance images by proposing an integrated image enhancement approach for face detection. The proposed approach is based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It can adjust the colour cast and maintain the luminance of the whole image at the same level. The research addresses the second issue relating to image retrieval by proposing a content-based image retrieval approach. The approach is based on the three welliii known algorithms: colour histogram, texture and moment invariants. Colour histogram is used to extract the colour features of an image. Gabor filter is used to extract the texture features and the moment invariant is used to extract the shape features of an image. The use of these three algorithms ensures that the proposed image retrieval approach produces results which are highly relevant to the content of an image query, by taking into account the three distinct features of the image and the similarity metrics based on Euclidean measure. In order to retrieve the most relevant images the proposed approach also employs a set of fuzzy heuristics to improve the quality of the results further. The integrated image enhancement approach is applied to the enhancement of low quality images produced by surveillance cameras. The performance of the proposed approach is evaluated by applying three face detection methods (skin colour based face detection, feature based face detection and image based face detection methods) to surveillance images before and after enhancement using the proposed approach. The results show a significant improvement in face detection when the proposed approach was applied. The performance of the content-based image retrieval approach is carried out using the standard Precision and Recall measures, and the results are compared with wellknown existing approaches. The results show the proposed approach perform s better than the well-known existing approaches.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:628932 |
| Date | January 2011 |
| Creators | Iqbal, K. |
| Publisher | Coventry University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://curve.coventry.ac.uk/open/items/ed5b98d3-84e6-4070-89cb-7ede2f0e9c0b/1 |
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