セルラ進化型回路網を用いた画像の領域分割とその認識

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: 2017/03/01

タイトル(英語): Image Segmentation and Recognition using Cellular Evolutionary Networks

著者名: 島崎　謙（横浜国立大学 大学院環境情報学府），長尾　智晴（横浜国立大学 大学院環境情報学府）

著者名(英語): Ken Shimazaki (Graduate School of Environment and Information Sciences, Yokohama National University), Tomoharu Nagao (Graduate School of Environment and Information Sciences, Yokohama National University)

キーワード: 画像処理，領域分割，画像認識，遺伝的アルゴリズム，セルラ進化型回路網　　image processing，image segmentation，image recognition，genetic algorithm，cellular evolutionary network

要約(英語): Image segmentation and image recognition are challenging processes, and the methods of merging those two processes like semantic segmentation have been studied. However, it is a lot of labor to construct the processes of segmentation and recognition manually, so automatic construction of those approaches using machine learning or evolutionary computation have been proposed. In this paper, we propose a model of pixel-wise image segmentation and recognition using Cellular Evolutionary Networks (CEN). Our proposed model is composed of a regular array of the identical feed forward networks, represented in Cartesian Genetic Programming (CGP), and each CGP connects with neighbor CGPs. In addition, we also propose a new model of CEN called CELLular Pyramid (CELLP), which operates multi resolution processing for an input image. We applied CEN and CELLP to some images and verified the effectiveness of our method.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.137 No.3 （2017） 特集：量子ビームによるナノバイオサイエンス技術

本誌掲載ページ: 502-512 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/137/3/137_502/_article/-char/ja/