The image processing handbook (2nd ed.)
The image processing handbook (2nd ed.)
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Detection using Geometrical Pixel Value Structures
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Automated Processing of Shoeprint Images Based on the Fourier Transform for Use in Forensic Science
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Automated encoding of footwear patterns for fast indexing
Image and Vision Computing
Footwear print retrieval system for real crime scene marks
IWCF'10 Proceedings of the 4th international conference on Computational forensics
Hi-index | 0.00 |
Shoeprints found on the crime scene contain useful information for the investigator: being able to identify the make and model of the shoe that left the mark on the crime scene is important for the culprit identification. Semi-automatic and automatic systems have already been proposed in the literature to face the problem, however all previous works have dealt with synthetic cases, i.e. shoe marks which have not been taken from a real crime scene but are artificially generated with different noise adding techniques. Here we propose a descriptor based on the Mahalanobis distance for the retrieval of shoeprint images. The performance test of the proposed descriptor is performed on real crime scenes shoe marks and the results are promising.