Titlebook: Computational Forensics; Second International Sargur N. Srihari,Katrin Franke Conference proceedings 2008 Springer-Verlag Berlin Heidelberg

daredevil

POWER

Computerized Matching of Shoeprints Based on Sole Patternased on manual coding with limited recognition ability, and the results are strongly dependent on the operator. In this paper, a shoeprint matching method based on PSD (power spectral density) and Zernike moment have been investigated. The PSD method aims at pressing images and the legible shoeprint

debouch

Shoe-Print Extraction from Latent Images Using CRFurface of its contact. Latent shoeprints can be used for identification of suspects in a forensic case by narrowing down the search space. This is done by elimination of the type of shoe, by matching it against a set of known shoeprints (captured impressions of many different types of shoes on a che

知識(shí)分子

Finding Identity Group “Fingerprints” in Documentsl way. The results of document classification experiments suggest that these group-level attributes provide better predictions of group affiliation than document-level attributes. Applications of this method for forensic authorship analysis are also discussed.

Kindle

Supporting Law Enforcement in Digital Communities through Natural Language Analysisal networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of today’s digital communities. This paper

先行

EPT

不連貫

Application of ,-Gram Distance in Digital Forensic Searchropriate fault tolerant distance measures are needed in order to detect evidence even if it has been previously distorted/partially erased from the search media. One of the appropriate fault-tolerant distance measures for this purpose is constrained edit distance, where the maximum numbers of consec

方便

Similarity Visualization for the Grouping of Forensic Speech Recordingsecordings are grouped using a clustering tool. The main disadvantage of such an approach is that in a bootstrapped scenario grouping errors accumulate. In this paper, we propose a visual approach to find similar speech recordings that probably stem from the same speaker. We first model the speech re

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