| Autor: |
B S Jennifer Chang, Q B S Cuong Luu, Victor E. Perlin, D. B. Johnson, Mitchell M. Rohde, Alice C. Thomas |
| Rok vydání: |
2011 |
| Předmět: |
|
| Zdroj: |
Journal of forensic sciences. 58(3) |
| ISSN: |
1556-4029 |
| Popis: |
It is often challenging to ascribe an objective measure of confidence for identifications based on surveillance imagery from a crime scene. The present work seeks to address this deficiency in the case of garment comparison evidence by developing a quantitative method for establishing a conservative lower bound on the likelihood ratio (LR) for identifications involving patterned garments. The method is based on statistical analysis of pattern offset measurements taken from a sample of garments of the same type (manufacturer, style, and size) as the seized evidence. The developed analysis framework was demonstrated on different types of garments over a range of modeled surveillance imaging scenarios with variable image quality; the lower bounds on the LRs ranged from approximately 10-1 to over 400-1. The statistical model was tested and validated through a large-scale empirical study involving both simulated and human observer-performed garment comparisons. Language: en |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
Plný text