Extraction and Recognition of Shoe Logos with a Wide Variety of Appearance Using Two-Stage Classifiers

• AOKI Kazunori

  Graduate School of Engineering, Mie University

• OHYAMA Wataru

  Graduate School of Engineering, Mie University

• WAKABAYASHI Tetsushi

  Graduate School of Engineering, Mie University

抄録

A logo is a symbolic presentation that is designed not only to identify a product manufacturer but also to attract the attention of shoppers. Shoe logos are a challenging subject for automatic extraction and recognition using image analysis techniques because they have characteristics that distinguish them from those of other products; that is, there is much within-class variation in the appearance of shoe logos. In this paper, we propose an automatic extraction and recognition method for shoe logos with a wide variety of appearance using a limited number of training samples. The proposed method employs maximally stable extremal regions for the initial region extraction, an iterative algorithm for region grouping, and gradient features and a support vector machine for logo recognition. The results of performance evaluation experiments using a logo dataset that consists of a wide variety of appearances show that the proposed method achieves promising performance for both logo extraction and recognition.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E101.D (5), 1325-1332, 2018-05-01

  一般社団法人 電子情報通信学会

キーワード

• logo extraction
• logo recognition
• maximally stable extremal regions
• gradient histogram features
• support vector machine

詳細情報

• CRID: 1390282679357630976
• NII論文ID: 130006729788
• DOI: 10.1587/transinf.2017mvp0026
• ISSN: 17451361
• ISSN: 09168532
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E101.D/5/E101.D_2017MVP0026/_pdf
• 本文言語コード: en
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