Recycled and Remarked Counterfeit Integrated Circuit Detection by Image-Processing-Based Package Texture and Indent Analysis

Wide proliferation of counterfeit integrated circuits (ICs) is a major global threat. Currently, the process of counterfeit IC detection is time-consuming and requires highly skilled subject matter experts. In this paper, we have developed an automated image-processing-based methodology for recycled and remarked counterfeit IC detection, using images acquired through an ordinary optical microscope or a digital camera. The methodology has two phases: first, identification of counterfeit IC is attempted by package texture comparison of a golden IC sample and the given sample. Then, for the ICs which have not been inferred to be counterfeit, an optional second phase where detection of position and size of indents (or cavities) on the IC package surface is performed. Compared to previously proposed techniques, the proposed technique is less computationally expensive and avoids expensive equipment such as a scanning electron microscope or X-ray tomograph. Experimental results demonstrate that the proposed methodology achieves high detection accuracy, and the results are supported by an unsupervised clustering approach.