スマートフォンカメラ撮影画像からの衣服素材の識別

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: 2022/12/01

タイトル(英語): Discrimination of Clothing Materials from Smartphone Camera Images

著者名: 小池　綾兵（名城大学），山田　啓一（名城大学）

著者名(英語): Ryohei Koike (Meijo University), Keiichi Yamada (Meijo University)

キーワード: 布素材，分類，畳み込みニューラルネットワーク，画像解像度_x000D_　　fabric material，classification，convolutional neural network，image resolution

要約(英語): Information on fabric material is necessary in washing and ironing clothing. However, indication on a care tag may peel off or the tag may come off due to deterioration over time. Discrimination of the material from the fabric itself is not easy for a general person. Estimating the material of an object is one of the challenging tasks in computer vision. This paper deals with the identification of cloth materials using computer vision. We studied a method to discriminate the fabric material from the image of clothing taken by a smartphone camera. First, we investigated the relationship between image resolution and discrimination accuracy using a convolutional neural network (CNN). As a result, we observed that the accuracy changes with resolution and that the resolution at which the accuracy is highest differs depending on the material. Based on these results, we proposed a fabric material discrimination method using multi-resolution images by combining two CNNs. As a result of the evaluation experiment, the proposed method discriminated six kinds of fabric materials with 87.1% accuracy, and the accuracy was significantly higher than that of the comparison method without using multi-resolution images.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.142 No.12 （2022） 特集：電気・電子・情報関係学会東海支部連合大会

本誌掲載ページ: 1275-1280 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/142/12/142_1275/_article/-char/ja/