電力検針票の自然画像を対象としたロバストな文字入力支援システムの開発と評価

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: 2023/02/01

タイトル(英語): Development and User Evaluation for a Robust Character Input Support System for Natural Images of Electricity Reading Slips

著者名: 五十嵐　俊治（東京大学 新領域環境棟374 生活支援工学研究室），小林　俊浩（北海道大学大学院工学研究科電子情報工学専攻），二瓶　美里（東京大学 新領域環境棟374 生活支援工学研究室）

著者名(英語): Toshiharu Igarashi (Assistive Technology Lab, Room 374, Department of Human & Engineered Environmental Studies, The University of Tokyo), Toshihiro Kobayashi (Department of Electronics and Information Engineering, Graduate School of Engineering, Hokkaido University), Misato Nihei (Assistive Technology Lab, Room 374, Department of Human & Engineered Environmental Studies, The University of Tokyo)

キーワード: 人間中心設計，画像認識，電力検針票，電気料金計算，ユーザビリティ評価　　human centered design，image recognition，electricity charge slip，utility charges，user evaluation

要約(英語): Text input, which is essential for a variety of applications, is one of the most difficult operations for older people. So, we propose a prototype to automatically detect and input text from a natural image taken from a user's smartphone. For the evaluation of the system, 232 photo data taken by the actual people were prepared. When all data was processed on the server, the average processing time was less than 10 seconds, and the overall recognition rate was over 94%. For user study, 20 healthy elderly people aged 65 years or older were collected. And, after conducting a simulation with the conventional typing system, the prototype in this proposal was asked to be used. The time required to complete each work was recorded, and the usability was evaluated using System Usability Scale (SUS).As a result, both the healthy older group and the MCI older group tended to shorten the task execution times and increase their SUS scores by using our application, compared to the conventional method. Also, comparing the SUS score with other Web applications, it is considered that usability is high as a prototype.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.143 No.2 （2023） 特集：エネルギー分野へ適用されたAI・IoT技術

本誌掲載ページ: 141-150 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/143/2/143_141/_article/-char/ja/