Footwear print retrieval system for real crime scene marks

Yi Tang; Sargur N. Srihari; Harish Kasiviswanathan; Jason J. Corso

doi:10.1007/978-3-642-19376-7_8

Footwear print retrieval system for real crime scene marks

Yi Tang
, Sargur N. Srihari
, Harish Kasiviswanathan
, Jason J. Corso

Department of Computer Science

SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers
Pages	88-100
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-19376-7_8
State	Published - 2011
Event	4th International Workshop on Computational Forensics, IWCF 2010 - Tokyo, Japan Duration: 11 Nov 2010 → 12 Nov 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6540 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Workshop on Computational Forensics, IWCF 2010
Country/Territory	Japan
City	Tokyo
Period	11/11/10 → 12/11/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

ARG
Content-based Image Retrieval
Footwear Impression Evidence
Footwear Print Distance
Hough transform

Access to Document

10.1007/978-3-642-19376-7_8

Cite this

Tang, Y., Srihari, S. N., Kasiviswanathan, H., & Corso, J. J. (2011). Footwear print retrieval system for real crime scene marks. In Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers (pp. 88-100). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6540 LNCS). https://doi.org/10.1007/978-3-642-19376-7_8

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title = "Footwear print retrieval system for real crime scene marks",

abstract = "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.",

keywords = "ARG, Content-based Image Retrieval, Footwear Impression Evidence, Footwear Print Distance, Hough transform",

author = "Yi Tang and Srihari, \{Sargur N.\} and Harish Kasiviswanathan and Corso, \{Jason J.\}",

year = "2011",

doi = "10.1007/978-3-642-19376-7\_8",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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note = "4th International Workshop on Computational Forensics, IWCF 2010 ; Conference date: 11-11-2010 Through 12-11-2010",

}

Tang, Y, Srihari, SN, Kasiviswanathan, H & Corso, JJ 2011, Footwear print retrieval system for real crime scene marks. in Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6540 LNCS, pp. 88-100, 4th International Workshop on Computational Forensics, IWCF 2010, Tokyo, Japan, 11/11/10. https://doi.org/10.1007/978-3-642-19376-7_8

Footwear print retrieval system for real crime scene marks. / Tang, Yi; Srihari, Sargur N.; Kasiviswanathan, Harish et al.
Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers. 2011. p. 88-100 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6540 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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M3 - Conference contribution

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers

T2 - 4th International Workshop on Computational Forensics, IWCF 2010

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ER -

Tang Y, Srihari SN, Kasiviswanathan H, Corso JJ. Footwear print retrieval system for real crime scene marks. In Computational Forensics - 4th International Workshop, IWCF 2010, Revised Selected Papers. 2011. p. 88-100. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-19376-7_8

Footwear print retrieval system for real crime scene marks

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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