Computational Forensics
Lecture notes in computer sciencePublished 1 January 2008
Hutchison, David, Weikum, Gerhard, Vardi, Moshe Y, Tygar, Doug, Terzopoulos, Demetri, Sudan, Madhu
Citations14
SJR quartileQ2
SJR score0.35
SNIP0.55
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
This Lecture Notes in Computer Science (LNCS) volume contains the papers presented at the Second International Workshop on Computational Forensics (IWCF 2008), held August 7–8, 2008. It was a great ho
Keywords
Computer Science
Lecture notes in computer scienceEvaluation of Graylevel-Features for Printing Technique Classification in High-Throughput Document Management Systems
25 Citations2008Christian Schulze, Marco Schreyer +2 more
It is shown that, under the given constraints of high-throughput systems, it is possible to determine the printing technique used to create a document.
Lecture notes in computer scienceShoe-Print Extraction from Latent Images Using CRF
4 Citations2008Veshnu Ramakrishnan, Manavender R. Malgireddy +1 more
An approach using Conditional Random Fields(CRFs) to solve the problem of labeling different regions of a latent image as foreground (shoeprint) and background and the model exploits the inherent long range dependencies that exist in the latentprint and hence is more robust than approaches using neural networks and other binarization algorithms.
Lecture notes in computer sciencePerson Identification Based on Barefoot 3D Sole Shape
2 Citations2008Michael Hild
3D foot sole shape of the human bare foot is adequate for person identification using principal component analysis and linear discriminant analysis in conjunction with 1---NN classification, and support vector machines in conjunctionwith output value thresholding.