用于IC认证、标识识别和伪造检测的标识检测和定位

Mukhil Azhagan Mallaiyan Sathiaseelan, Manoj Yasaswi Vutukuru, Shajib Ghosh, Olivia P. Paradis, M. Tehranipoor, N. Asadizanjani, David Crandall
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引用次数: 1

摘要

在本文中,我们提出了一种新的印刷电路板(PCB)标识检测方案。随着越来越多的PCB假冒和特洛伊木马的发生,拥有一个快速,自动化的PCB保证工具是时间的需要。标识检测和验证是PCB保证和防伪的重要步骤。此外,由于标识干扰,pcb中的文本识别变得困难,这也可以通过我们提出的解决方案来解决。我们描述了基于深度神经网络(DNN)的算法以及所使用的数据集的描述。最后,我们展示了使用通用目标检测指标的图像和定性结果,以证明我们提出的方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Logo Detection and Localization for IC Authentication, Marking Recognition, and Counterfeit Detection
In this manuscript, we present a new solution to logo detection on printed circuit boards (PCB). With the growing incidence of PCB counterfeits and Trojans, having a quick, automated PCB assurance tool is the need of the hour. Logo detection and verification is an important step in PCB assurance and counterfeit detection. In addition, text recognition in PCBs is made difficult due to logo interference, which can also be solved with our proposed solution. We describe our Deep Neural Network (DNN)-based algorithm along with a description of the dataset used. Finally, we present images as well as qualitative results using common object detection metrics to demonstrate the performance of our proposed approach.
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