Fundamentals of digital image processing
Fundamentals of digital image processing
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
Thresholding of noisy shoeprint images based on pixel context
Pattern Recognition Letters
Computerized Matching of Shoeprints Based on Sole Pattern
IWCF '08 Proceedings of the 2nd international workshop on Computational Forensics
Automated encoding of footwear patterns for fast indexing
Image and Vision Computing
A Texture Based Shoe Retrieval System for Shoe Marks of Real Crime Scenes
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
LS Footwear Database - Evaluating Automated Footwear Pattern Analysis
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Retrieval of shoemarks using Harris points and sift descriptor
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A texture recognition system of real shoe marks taken from crime scenes
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Footwear print retrieval system for real crime scene marks
IWCF'10 Proceedings of the 4th international conference on Computational forensics
Dual phase learning for large scale video gait recognition
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Automatic extraction and classification of footwear patterns
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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The development of a system for automatically sorting a database of shoeprint images based on the outsole pattern in response to a reference shoeprint image is presented. The database images are sorted so that those from the same pattern group as the reference shoeprint are likely to be at the start of the list. A database of 476 complete shoeprint images belonging to 140 pattern groups was established with each group containing two or more examples. A panel of human observers performed the grouping of the images into pattern categories. Tests of the system using the database showed that the first-ranked database image belongs to the same pattern category as the reference image 65 percent of the time and that a correct match appears within the first 5 percent of the sorted images 87 percent of the time. The system has translational and rotational invariance so that the spatial positioning of the reference shoeprint images does not have to correspond with the spatial positioning of the shoeprint images of the database. The performance of the system for matching partial-prints was also determined.