Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors

Al-Maadeed, Somaya, Bouridane, Ahmed, Crookes, Danny and Nibouche, Omar (2014) Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors. Integrated Computer-Aided Engineering, 22 (1). pp. 41-58. ISSN 1069-2509

Full text not available from this repository. (Request a copy)

Abstract

Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.

Item Type:	Article
Additional Information:	Published online 11-11-2014 ahead of print
Uncontrolled Keywords:	automatic shoeprint recognition; Multiscale point detector; shoeprint retrieval; SIFT descriptor
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	06 Feb 2015 14:22
Last Modified:	13 Oct 2019 00:37
URI:	http://nrl.northumbria.ac.uk/id/eprint/21325

Downloads