Pattern recognition of Vehicle Logo using Tchebichef and Legendre moment

Foo Chong Soon, Hui Ying Khaw, Joon Huang Chuah

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

In this paper, we propose a Vehicle Logo Recognition (VLR) approach which uses moment invariant for feature extraction. Moment invariants and Minimum-Mean Distance (MMD) classifier are adopted to recognize six different types of vehicle logos from a public dataset. Vehicle logos obtained from coarse and fine segmentation, are recognized using Tchebichef and Legendre moment invariants. In either coarse or fine segmented vehicle logo images, Tchebichef moment invariants perform better than the Legendre's. With the experimental accuracy results of 88.3% on the 240 dataset images of six different types of vehicle logos, it has demonstrated the effectiveness of the proposed method in recognizing the fine segmented vehicle logo, which supports the use of the system for real application.

Original languageEnglish
Title of host publication2015 IEEE Student Conference on Research and Development, SCOReD 2015
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages82-86
Number of pages5
ISBN (Electronic)9781467395724
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventIEEE Student Conference on Research and Development (SCOReD) 2015 - Kuala Lumpur, Malaysia
Duration: 13 Dec 201514 Dec 2015
https://ieeexplore.ieee.org/xpl/conhome/7445582/proceeding (Proceedings)

Conference

ConferenceIEEE Student Conference on Research and Development (SCOReD) 2015
Abbreviated titleSCOReD 2015
Country/TerritoryMalaysia
CityKuala Lumpur
Period13/12/1514/12/15
Internet address

Keywords

  • Legendre
  • Minimum-Mean Distance (MMD)
  • Tchebichef
  • Vehicle-Logo Recognition (VLR)

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