TY - GEN
T1 - Footwear print retrieval system for real crime scene marks
AU - Tang, Yi
AU - Srihari, Sargur N.
AU - Kasiviswanathan, Harish
AU - Corso, Jason J.
PY - 2011
Y1 - 2011
N2 - Footwear impression evidence has been gaining increasing importance in forensic investigation. The most challenging task for a forensic examiner is to work with highly degraded footwear marks and match them to the most similar footwear print available in the database. Retrieval process from a large database can be made significantly faster if the database footwear prints are clustered beforehand. In this paper we propose a footwear print retrieval system which uses the fundamental shapes in shoes like lines, circles and ellipses as features and retrieves the most similar print from a clustered database. Prints in the database are clustered based on outsole patterns. Each footwear print pattern is characterized by the combination of shape features and represented by an Attributed Relational Graph. Similarity between prints is computed using Footwear Print Distance. The proposed system is invariant to distortions like scale, rotation, translation and works well with the partial prints, color prints and crime scene marks.
AB - Footwear impression evidence has been gaining increasing importance in forensic investigation. The most challenging task for a forensic examiner is to work with highly degraded footwear marks and match them to the most similar footwear print available in the database. Retrieval process from a large database can be made significantly faster if the database footwear prints are clustered beforehand. In this paper we propose a footwear print retrieval system which uses the fundamental shapes in shoes like lines, circles and ellipses as features and retrieves the most similar print from a clustered database. Prints in the database are clustered based on outsole patterns. Each footwear print pattern is characterized by the combination of shape features and represented by an Attributed Relational Graph. Similarity between prints is computed using Footwear Print Distance. The proposed system is invariant to distortions like scale, rotation, translation and works well with the partial prints, color prints and crime scene marks.
KW - ARG
KW - Content-based Image Retrieval
KW - Footwear Impression Evidence
KW - Footwear Print Distance
KW - Hough transform
UR - http://www.scopus.com/inward/record.url?scp=79952261178&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952261178&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-19376-7_8
DO - 10.1007/978-3-642-19376-7_8
M3 - Conference contribution
AN - SCOPUS:79952261178
SN - 9783642193750
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 88
EP - 100
BT - Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers
T2 - 4th International Workshop on Computational Forensics, IWCF 2010
Y2 - 11 November 2010 through 12 November 2010
ER -