Counterfeit Detection Using Machine Learning and Deep Learning
With the advancements in smartphone capabilities, digital anti-counterfeiting technologies such as copy detection patterns and surface fingerprints are replacing traditional solutions (e.g. holograms, security inks). These digital authentication techniques have numerous advantages: they provide intrinsic security, rely on existing production processes, and authentication can potentially be performed by anyone with a smartphone. However, pushing the boundaries in terms of security and ease of verification raises a number of challenges, which are best addressed by machine learning and deep learning techniques.
Date and Time
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- Date: 30 Apr 2025
- Time: 05:00 PM UTC to 06:00 PM UTC
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Hong Zhao (zhao@fdu.edu), Alfredo Tan (tan@fdu.edu)
- Co-sponsored by Fairleigh Dickinson University
Speakers
Dr. Justin Picard of Scantrust
Counterfeit Detection Using Machine Learning and Deep Learning
With the advancements in smartphone capabilities, digital anti-counterfeiting technologies such as copy detection patterns and surface fingerprints are replacing traditional solutions (e.g. holograms, security inks). These digital authentication techniques have numerous advantages: they provide intrinsic security, rely on existing production processes, and authentication can potentially be performed by anyone with a smartphone. However, pushing the boundaries in terms of security and ease of verification raises a number of challenges, which are best addressed by machine learning and deep learning techniques.
Biography:
Dr. Justin Picard (a Senior Member of IEEE) is the co-founder and Chief Technology Officer at Scantrust, a leading anti-counterfeiting and traceability software company. Dr. Picard is the inventor of the copy detection pattern, a digital authentication technology for detecting product and document counterfeiting. Copy detection patterns are used to protect billions of products each year, and are a topic of active research within the IEEE Signal Processing Information Forensics and Security community. Dr. Picard attended Polytechnique Montréal, where he received his B.S. degree in physics engineering (1990-1994), and his MSc in electronics engineering (1994-1997). He received a PhD in computer science from the University of Neuchâtel (1996-2000), before attending the École Polytechnique Fédérale de Lausanne (EPFL) for postdoctoral research in digital watermarking (2000-2001). Dr. Picard was a research and development engineer at Mediasec Technologies in Rhode Island (2001-2004), the head of research and development at Thomson Technicolor in Germany (2004-2006), and later the chief scientist at Advanced Track & Trace in France (2006-2013). In 2014, he co-founded Scantrust in Switzerland, after filing a patent on a QR Code which secures against counterfeit attempts. He was chief executive officer of the company until 2017, then took the role of Chief Technology Officer.
Dr. Picard is a member of the Organisation for Economic Co-operation and Development Task Force on Countering Illicit Trade (2012-), and a member of the network of experts at the Global Initiative Against Transnational Organized Crime (2016-). He was selected as World Economic Forum Technology (WEF) Pioneer (2009), and served as a member of the WEF Global Agenda Council on Illicit Trade (2009-2014). He is a member of the GS1 Digital Link technical committee, and an advisor to the European Union Intellectual Property Organization (EUIPO) on anti-counterfeiting technologies. He is also a co-founder of the non-governmental organization Black Market Watch, where he developed a methodology to assess the impacts of illicit trade. Dr. Picard has more than 25 patents and patent applications related to anti-counterfeiting technologies, secure traceability of documents and products, and digital image and video watermarking.
Dr. Picard was co-organizer of the special session on “Forensics and Security of Physical Objects” at the 2021 IEEE Workshop on Information Forensics and Security (WIFS). He is a reviewer for WIFS, and is on the program committee of the ACM Symposium on document engineering. Dr. Picard’s lecture topics include signal processing techniques for authentication and security of physical objects, image processing techniques for product authentication with smartphones, and counterfeit detection using machine learning and deep learning.
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Agenda
Fairleigh Dickinson University
1000 River Road, Building: Muscarelle Center, Room Number: 105
Teaneck, New Jersey, United States 07666
For additional information about the venue and parking, please contact
Dr. Hong Zhao