Mourad Gueham

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In this paper, a method for automatically recognizing partial shoeprint images for use in forensic science is presented. The technique uses the phase-only correlation (POC) for shoeprints matching. The main advantage of this method is its capability to match low quality shoeprint images accurately and efficiently. In order to achieve superior performance,(More)
One of the most difficult problems in automatic shoeprint classification is the matching of partial shoeprint images. This task becomes more challenging in the presence of geometric distortions (e.g. translated and/or rotated partial prints). In this paper, we evaluate the performance of Advanced Correlation Filters (ACFs) for the automatic classification(More)
In this paper, we propose a solution for the problem of rotated partial shoeprint retrieval, based on the combined use of local points of interest and SIFT descriptor. Once the generated features are encoded using SIFT descriptor, matching is carried out using RANSAC to estimate a transformation model and establish the number of its inliers which is then(More)
In this work we investigate the performance of Advanced Correlation Filters (ACFs) in the automatic classification of partial shoeprints for use in forensic science. In particular, the Optimum Trade-off Synthetic Discriminant Function (OTSDF) filter is used to match low quality partial shoeprints. Experiments were conducted on a database of images of 100(More)
This paper deals with the retrieval of scene-of-crime (or scene) shoeprint images from a reference database of shoeprint images by using a new local feature detector and an improved local feature descriptor. Our approach is based on novel modifications and improvements of a few recent techniques in this area: (1) the scale adapted Harris detector, which is(More)
In this paper, we suggest a solution for the problem of scene-of-crime shoeprints retrieval based on the use of multi-scale Harris points, which are a set of very distinctive points of interest in an image, combined with SIFT descriptor. We show that such combination can overcome the issue of retrieval of partial prints in the presence of scale and rotation(More)
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