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0907学术讲座

日期:2012年09月03日     本文发布:www.3499.com

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学院邀请 加州KLA-Tencor企业高级算法工程师(Senior Algorithm Engineer)王永昌博士来校讲座。

讲座时间:2012年9月7日(周五)上午10:30

地点:基础教学大楼B座206

题目:Novel Approaches in Structured Light Illumination and Semi-conduct Inspection

摘要:Structured light illumination by means of phase shifting patterns is a widely employed method for 3-D image acquisition that is robust to ambient light and object albedo but may be especially susceptible to sensor and environment noise. In order to improve the signal to noise ratio (SNR), one possible approach is to maximize the pattern’s SNR, and another approach is to employ the high frequency patterns. In this presentation, we first study the specific technique of phase measuring profilometry (PMP) and the maximization of a patterns signal to noise ratio (SNR). By treating the design of an N-pattern PMP process as placing points in an N-dimensional coding space, we define a patterns SNR in terms of a pattern sets computational length and the number of coded phase periods in the projected patterns. Then, without introducing phase ambiguities, we propose a so-called edge-pattern strategy that maximizes the computational length and number of periods. Theoretically, the edge-pattern technique improves the SNR by 1.2381 times when using three component patterns and 15.5421 times when using five patterns. Secondly, we will focus on high frequency patterns. In general, the high frequency patterns improve the SNR. However, high pattern frequencies introduce ambiguities during phase unwrapping. In this presentation, we introduce a process for embedding a period cue into the projected pattern set without reducing the signal-to-noise ratio. As a result, each period of the high frequency signal can be identified. The proposed method can unwrap high frequency phase and achieve high measurement precision without increasing the pattern number. Therefore, the proposed method can significantly benefit real-time applications. The method is verified by theoretical and experimental analysis using prototype system built to achieve 120 fps at the resolution of 640 x 480. We implement the novel approaches by using the Look-Up Table method for real-time data processing. In conclusion, a real-time system and a 3D fingerprinting system are presented to demonstrate the advantages of the proposed methods.

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In the second part of the presentation, we will focus on the semi-conduct inspection. Specifically, we will introduce the wafer and disc inspection system, which simultaneously measures surface reflectivity and topography for automatic defect detection and classification. The system’s inspection technology combines scatterometry, ellipsometry, reflectometry, and topographical analysis to non-destructively inspect the surfaces for defects, and film thickness uniformity. Employing advanced adaptive filter scheme, the algorithm finds out the defects located on the varying surfaces of disc and wafer with high accuracy and purity. The SVM machine learning technology is developed to achieve auto and accurate classification of the defects. Currently, the inspection tools we introduce dominate the world market and represent the most advanced technology in the industry.

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