Extraction and Recognition of Shoe Logos with a Wide Variety of Appearance Using Two-Stage Classifiers
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.5 pp.1325-1332
- Publication Date
- 2018/05/01
- Publicized
- 2018/02/16
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017MVP0026
- Type of Manuscript
- Special Section PAPER (Special Section on Machine Vision and its Applications)
- Category
- Machine Vision and its Applications
Authors
Kazunori AOKI
Mie University
Wataru OHYAMA
Mie University
Tetsushi WAKABAYASHI
Mie University
Keyword
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Kazunori AOKI, Wataru OHYAMA, Tetsushi WAKABAYASHI, "Extraction and Recognition of Shoe Logos with a Wide Variety of Appearance Using Two-Stage Classifiers" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 5, pp. 1325-1332, May 2018, doi: 10.1587/transinf.2017MVP0026.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017MVP0026/_p
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@ARTICLE{e101-d_5_1325,
author={Kazunori AOKI, Wataru OHYAMA, Tetsushi WAKABAYASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Extraction and Recognition of Shoe Logos with a Wide Variety of Appearance Using Two-Stage Classifiers},
year={2018},
volume={E101-D},
number={5},
pages={1325-1332},
abstract={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.},
keywords={},
doi={10.1587/transinf.2017MVP0026},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Extraction and Recognition of Shoe Logos with a Wide Variety of Appearance Using Two-Stage Classifiers
T2 - IEICE TRANSACTIONS on Information
SP - 1325
EP - 1332
AU - Kazunori AOKI
AU - Wataru OHYAMA
AU - Tetsushi WAKABAYASHI
PY - 2018
DO - 10.1587/transinf.2017MVP0026
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2018
AB - 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.
ER -
English
