Extraction and recognition of shoe logos with a wide variety of appearance using two-stage classifiers

Kazunori Aoki, Wataru Ohyama, Tetsushi Wakabayashi

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1325-1332
Number of pages8
JournalIEICE Transactions on Information and Systems
VolumeE101D
Issue number5
DOIs
Publication statusPublished - May 2018

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Extraction and recognition of shoe logos with a wide variety of appearance using two-stage classifiers'. Together they form a unique fingerprint.

Cite this