Writer Identification Using Inexpensive Signal Processing Techniques

We propose to use novel and classical audio and text signal-processing and otherwise techniques for "inexpensive" fast writer identification tasks of scanned hand-written documents "visually". The "inexpensive" refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate "visual" identification by "looking" at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.Comment: 9 pages; 1 figure; presented at CISSE'09 at http://conference.cisse2009.org/proceedings.aspx ; includes the the application source code; based on MARF described in arXiv:0905.123

MARF: Modular Audio Recognition Framework (in French)

Le Modular Audio Recognition Framework (MARF) concu en 2002, est une plateforme de recherche open-source et une collection de composants avec des algorithmes pour le traitement de la voix, le son, la parole, et l'écriture et de langues naturelles (TALN) MARF a été crée en Java et organisé sous forme de modules extensible qui facilite l'addition de nouvelles algorithmes. MARF peut être utilisé comme une bibliothèque dans un application ou comme une base de support à l'apprentisage et en extension. MARF a aussi été publié dans les plusieurs articles de conférence avec les detailles scientifiques dedant. De la documentation détaillée et la référence d'API en format javadoc sont disponibles étant donné que le projet tente d'être bien-documenté. MARF et ses applications sont déployés sous une licence BSD

Encoding Forensic Multimedia Evidence from MARF Applications as Forensic Lucid Expressions

In this work we summarize biometric evidence as well as file type evidence extraction “exported” as formal Forensic Lucid language expression in the form of higher-order intensional contexts for further case analysis by a system that interprets Forensic Lucid expressions for claim verification and event reconstruction. The digital evidence is exported from the Modular Audio Recognition Framework (MARF)’s applications runs on a set of data comprising biometric voice recordings for speaker, gender, spoken accent, etc. as well as more general file type analysis using signal and pattern recognition processing techniques. The focus is in translation aspect of the extracted evidence into formal Forensic Lucid expressions for further analysis

LifeCLEF Bird Identification Task 2015

International audienceThe LifeCLEF bird identification task provides a testbed for a system-oriented evaluation of 999 bird species identification. The main originality of this data is that it was specifically built through a citizen science initiative conducted by Xeno-Canto, an international social network of amateur and expert ornithologists. This makes the task closer to the conditions of a real-world application than previous, similar initiatives. This overview presents the resources and the assessments of the task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results

Towards Security Hardening of Scientific Demand-Driven and Pipelined Distributed Computing Systems

This work highlights and takes aim at the most critical security aspects required for two different types of distributed systems for scientific computation. It covers two open-source systems written in Java: a demand-driven system - general intensional programming system (GIPSY) and a pipelined system - distributed modular audio recognition framework (DMARF), which are the distributed scientific computational engines used as case studies with respect to the security aspects. More specific goals include data/demand integrity, data/demand origin authentication, confidentiality, high availability, and malicious code detection. We address some of the goals to a degree, some with the Java data security framework (JDSF) as a work-in- progress