多次元モルフォロジーに基づく頑強なテクスチャ特徴量の抽出と応用

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: 2014/02/01

タイトル(英語): Robust Feature Extraction from Texture Based on Multi-dimensional Morphology and Its Application

著者名: 武井　彰大（東京電機大学大学院 工学研究科），和田　成夫（東京電機大学大学院 工学研究科）

著者名(英語): Syota Takei (Graduate School of Engineering, Tokyo Denki University), Shigeo Wada (Graduate School of Engineering, Tokyo Denki University)

キーワード: テクスチャ，幾何的変形，モルフォロジー，パターンスペクトル，共起行列　　Texture，Geometric distortion，Morphology，Pattern spectrum，Co-occurrence Matrix

要約(英語): In this paper, we propose a robust feature extraction method for color texture image based on multi-dimensional morphology. Multi-value co-occurrence matrix of multi-value morphology pattern spectrum of skeletons is used to represent texture structure. Color features are also extracted from RGB components based on similar binary morphology pattern spectrum. The extracted feature vectors have robustness to geometric distortions such as shift, rotation, scaling, skew, projection and their combinations. In simulations, robustness performance of the proposed method is verified to show the effectiveness under various distortion conditions. The effectiveness is examined by applying to image retrieval and classification systems. Accuracy of retrieval and classification is evaluated compared with those of HLAC based approach.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.2 （2014） 特集：知覚情報技術の最前線

本誌掲載ページ: 225-232 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/2/134_225/_article/-char/ja/