A Database for Counterfeit Electronics and Automatic Defect Detection Based on Image processing and Machine Learning
A Database for Counterfeit Electronics and Automatic Defect Detection Based on Image processing and Machine Learning
Thursday, November 10, 2016: 10:15 AM
108 (Fort Worth Convention Center)
Summary:
Counterfeiting is becoming an increasing concern for businesses and governments as greater numbers of counterfeit integrated circuits (IC) infiltrate the global market. There is an ongoing effort in experimental and national labs inside the US to detect and prevent such counterfeits in the most efficient time period. However, there is still a missing piece to automatically detect and properly keep record of detected counterfeit ICs. Here, we introduce a web application database that allows sharing previous examples of counterfeits through an online database and obtaining statistics regarding to the prevalence of known defects. This database should also enable development of image processing and machine learning techniques to detect different physical defects that automatically determine whether or not an IC is counterfeit.
Counterfeiting is becoming an increasing concern for businesses and governments as greater numbers of counterfeit integrated circuits (IC) infiltrate the global market. There is an ongoing effort in experimental and national labs inside the US to detect and prevent such counterfeits in the most efficient time period. However, there is still a missing piece to automatically detect and properly keep record of detected counterfeit ICs. Here, we introduce a web application database that allows sharing previous examples of counterfeits through an online database and obtaining statistics regarding to the prevalence of known defects. This database should also enable development of image processing and machine learning techniques to detect different physical defects that automatically determine whether or not an IC is counterfeit.