A Study on Robust SEM Photometric Stereo Using Two BSE Detectors

• 資料種別: 博士論文
• タイトル: A Study on Robust SEM Photometric Stereo Using Two BSE Detectors
• 著者・編者: 陳, 德山
• 著者標目: 陳, 德山
• 出版事項: Hokkaido University
• 出版年月日等: 2014-03-25
• 出版年（W3CDTF）: 2014-03-25
• 並列タイトル等: 2つのBSE検出器を用いたロバストSEM照度差ステレオに関する研究
• 寄与者: 金子, 俊一; 小野里, 雅彦; 田中, 孝之
• 授与機関名: 北海道大学
• 授与年月日: 2014-03-25
• 授与年月日（W3CDTF）: 2014-03-25
• 報告番号: 甲第11315号
• 学位: 博士(情報科学)
• 博論授与番号: 甲第11315号
• 本文の言語コード: eng
• 著者別名: Chen, Deshan
• 件名標目: Scanning Electron Microscope (SEM); Shape Reconstruction; Shadowing Compensation model; Backscattering Electron; Variational Method
• NDC: 500
• 対象利用者: 一般
• 一般注記: This thesis presents a novel robust SEM photometric stereo method using two backscattered electron detectors. Robustness is one of the most important factors for practical applications. Although SEM photometric stereo has gained a lot of attention and been extensively studied, the robustness remains a very interesting challenge. Among ill factors, we realize that shadowing and noise problems are almost inherent in SEM photometric stereo. In particular, the shadowing effects generally give rise to significant errors in the reconstructed shapes. The present work is thereby devoted to developing SEM photometric stereo so that it can automatically handle such ill factors.For dealing with shadowing effects, we introduce a shadowing compensation model though modeling image intensities in both cases of absence and presence of shadowing based mainly on angle distribution of backscattered electrons. This model relates the underlying shadowless image to the observed one by the corresponding detection ratio. The detection ratio has modeled the shadowing generation process by means ofshadowing angles, which reflects the amount of occluded backscattered electrons. One advantage of the shadowing compensation model is that it is no need for us to treat the regions with shadowing errors separately from those without such errors, because the shadowless case is the special case of shadowing. Therefore, in contrast to some other approaches, the proposed method does not require an image segmentation process toextract shadowing regions, which is substantially difficult to implement automatically.The model has already provided an important cue to eliminate shadowing errors by means of inferring the shadowless images from the observed one if the shadowing angles can be obtained.With the shadowing compensation model and gradient estimation equation, we formulate the proposed robust shape reconstruction into a constrained optimization problem via a variational approach. The objective functional consists of two terms. One is the fidelity term that is to guarantee the gradient of reconstructed shape should be consistent with the gradient data. In particular, the gradient data are evaluated fromshadowless images so as to eliminate shadowing errors. In addition, shadowless images are related to the corresponding observed ones through our shadowing compensation model, which forms the constraints. The second term is total variation prior to penalize the roughness of the solution and consequently make our method be robust to noise influence arising in the data term. We adopt an iterative scheme to solve the problem,which performs commutatively between the compensation of image intensities and the modification of the corresponding 3D shape, can effectively provide both an accurate 3D shape and compensated shadowless images after convergence.We present an extension to the shadowing compensation model in order to improve the model accuracy in the shadowing regions on the general curved surfaces. The extended model removes the earlier restrictive assumption that the shadowing effects exist only on horizontal surfaces. This model is developed in an analogous way through modeling image intensities in both the absence and presence of shadowing. A numericalsolution is proposed to resolve the implicit expressions for double integrals in the model.Compared to the previous shadowing compensation model, the extended model can be more accurate when applied to shadowing regions on surfaces having large inclinations.Experimental results demonstrate the robustness and effectiveness of our proposed methods. Compared to the traditional methods, reconstructed 3D shapes can achievehigher accuracy. Furthermore, the resulting compensated images provide a potential opportunity for improving the imaging performance of SEM devices.; (主査) 教授 金子 俊一, 教授 小野里 雅彦, 准教授 田中 孝之; 情報科学研究科（システム情報科学専攻）
• DOI: 10.14943/doctoral.k11315; https://doi.org/10.14943/doctoral.k11315
• 国立国会図書館永続的識別子: info:ndljp/pid/8949792; https://dl.ndl.go.jp/pid/8949792
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文; https://dl.ndl.go.jp/collections/A00014
• 収集根拠: 博士論文（自動収集）
• 公開開始日（W3CDTF）: 2015-03-03
• 受理日（W3CDTF）: 2015-02-03T05:25:05+09:00
• 作成日（W3CDTF）: 2014-03
• 記録形式（IMT）: PDF
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: http://dx.doi.org/10.14943/doctoral.k11315; http://hdl.handle.net/2115/55664
• 参照（URI）: http://hdl.handle.net/2115/55663
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: This thesis presents a novel robust SEM photometric stereo method using two backscattered electron detectors. Robustness is one of the most important ...