Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis

Darren K. Emge; Tülay Adalı

doi:10.1117/12.2053374

Translator Disclaimer

13 June 2014 Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis

Darren K. Emge, Tülay Adalı

Author Affiliations +

Proceedings Volume 9092, Signal and Data Processing of Small Targets 2014; 909207 (2014) https://doi.org/10.1117/12.2053374
Event: SPIE Defense + Security, 2014, Baltimore, Maryland, United States

Abstract

As the availability and use of imaging methodologies continues to increase, there is a fundamental need to jointly analyze data that is collected from multiple modalities. This analysis is further complicated when, the size or resolution of the images differ, implying that the observation lengths of each of modality can be highly varying. To address this expanding landscape, we introduce the multiset singular value decomposition (MSVD), which can perform a joint analysis on any number of modalities regardless of their individual observation lengths. Through simulations, the inter modal relationships across the different modalities which are revealed by the MSVD are shown. We apply the MSVD to forensic fingerprint analysis, showing that MSVD joint analysis successfully identifies relevant similarities for further analysis, significantly reducing the processing time required. This reduction, takes this technique from a laboratory method to a useful forensic tool with applications across the law enforcement and security regimes.

Citation Download Citation

Darren K. Emge and Tülay Adalı "Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis", Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 909207 (13 June 2014); https://doi.org/10.1117/12.2053374

ACCESS THE FULL ARTICLE