Sciometrics specializes in patented object recognition technologies, primarily in support of the global military, intelligence, and law enforcement communities. The technology evolved out of optical character recognition technology and has since resulted in advancements within multilingual handwriting biometrics, latent print matching, tool mark analysis, and other related pattern matching capabilities.
Over the last decade, Sciometrics has used its technologies to perform a number of pattern recognition research and development projects for intelligence and law enforcement agencies. Commercialization of the algorithms for more general distribution has taken place over the last several years, resulting in our four current products: LatentSleuth our advanced latent print analysis product, Slapshot, our smartphone fingerprint capture app, Digital Lift, our smartphone latent lift capture app, and FLASH ID, our industry leading handwriting biometric product.
Our products and technologies are in use by the Federal Bureau of Investigation, the Department of Defense, and other state, local, and international agencies.
Over the last decade, Sciometrics has used its graphing techniques to perform a number of pattern recognition research and development projects for intelligence and law enforcement agencies.
Latent Fingerprint Matching: using fragments - as small as 6x6 millimeters – which did not contain enough minutiae for traditional matching techniques.
Mobile Biometrics: imaging, ingestion and matching of biometrics using standard mobile sensors, i.e., an Android smartphone.
Handwriting Analysis: handwriting biometrics in multiple languages.
Face: using graphing techniques to correct for gaze angles in surveillance photos.
Voice: matching voice snippets.
Biometric Fusion: combining face, small handwriting samples, and small latent fingerprints.
Pollen Identification: analysis of 3D pollen images to determine geographic origin of suspect materials.
Tool Mark identification: analysis and identification of tool marks related to crime scenes.
Object recognition and extraction: automated recognition of objects in large image galleries and separating them from backgrounds scenes.
Mark Walch is the President of Sciometrics LLC, where he brings more than 25 years of technical and managerial experience. In this role, Mr. Walch oversees development of a variety of technologies related to the efficient and effective capture of data from images.
Mr. Walch is the principal architect of Pictographic pattern-matching methods, and has developed innovative Optical Character Recognition techniques that have been used to read hand print and cursive script for the U.S. Postal Service. Derivatives of these techniques have been used successfully to register independent vector data sets for upgrading map data on behalf of the U.S. Census Bureau.
Mr. Walch has also developed several automated techniques for accurate and cost-effective data capture from handwritten and printed forms, and pioneered the concept of “directed workflow”—a method for streamlining the way human operators review large quantities of data.
Mr. Walch holds advanced degrees from the University of Michigan and Yale University.
Daniel Gantz is a senior software engineer at Sciometrics LLC. Daniel has worked for this group since graduating The University of Virginia's school of engineering in 2008 with a bachelor of science in computer science.
Daniel has helped as well as lead development for a number of different biometric systems from their R&D inception to their evolution into industrial level applications. The nature of these biometric systems include latent fingerprint, tool-mark and handwriting identification.
A Full Professor of Statistics, Dr. Gantz was the founding Chair of the AIT Department and now serves as the Director of the Document Forensics Laboratory. He has also as served as Interim Associate Dean for Undergraduate Studies in the Volgenau School at GMU. Dr. Gantz is currently applying his cutting edge analysis of handwriting to multi-language document exploitation and biometric identification. He has been active in the research and application of geographic information systems, modeling systems, and decision support systems to transportation demand management and traffic mitigation. Other areas of research include analysis of latent fingerprints, the relationship between TB incidence and socioeconomic factors, surveillance systems to track infection, computer performance evaluation, flight design, and litigation related analyses.
Dr. Gantz earned his Ph.D. and M.A. in Mathematics at the University of Rochester, and his B.A. in Mathematics at Fordham University.