Efficient Parameter Optimization by Applying Estimation Error Reduction to Design of Experiments for Image Processing

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/01/01

タイトル(英語): Efficient Parameter Optimization by Applying Estimation Error Reduction to Design of Experiments for Image Processing

著者名: Yohei Minekawa (Yokohama Research Laboratory, Hitachi, Ltd.), Kenji Nakahira (Yokohama Research Laboratory, Hitachi, Ltd.), Ryo Nakagaki (Yokohama Research Laboratory, Hitachi, Ltd.), Yuji Takagi (Yokohama Research Laboratory, Hitachi, Ltd.)

著者名(英語): Yohei Minekawa (Yokohama Research Laboratory, Hitachi, Ltd.), Kenji Nakahira (Yokohama Research Laboratory, Hitachi, Ltd.), Ryo Nakagaki (Yokohama Research Laboratory, Hitachi, Ltd.), Yuji Takagi (Yokohama Research Laboratory, Hitachi, Ltd.)

キーワード: Parameter optimization，Design of experiments，Orthogonal array table，Area extraction，Mapping function

要約(英語): An efficient method for optimizing the parameters used for image processing is described that applies estimation error reduction to design of experiments (DOE). The traditional DOE optimization method is used to estimate the evaluation scores of all parameter sets and to rank them using a small number of actual scores. Because the search for the optimal parameter set is done in the order of the estimated scores for all parameter sets, the ranking accuracy, which strongly depends on the estimation error, is important. We introduce a function for reducing the estimation errors for the higher ranked parameter sets. The proposed parameter optimization method was evaluated by applying it to parameter optimization for industrial image defect area extraction. Evaluation using three datasets showed that the parameter sets selected by the proposed method had close to the highest actual score and that the number of image processings was 1/57 that of a full search procedure.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.1 （2013） 特集：2012 Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2012)

本誌掲載ページ: 111-116 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/1/133_111/_article/-char/ja/