Vehicle Logo Recognition Based on Local Feature Descriptor

Sheng Ke Wang; Lili Liu; Xiaowei Xu

doi:10.4028/www.scientific.net/AMM.263-266.2418

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Vehicle Logo Recognition Based on Local Feature...

Vehicle Logo Recognition Based on Local Feature Descriptor

Abstract:

In this paper, we present a comparison of the scale-invariant feature transforms (SIFT)-based feature-matching scheme and the speeded up robust features (SURF)-based feature-matching scheme in the field of vehicle logo recognition. We capture a set of logo images which are varied in illumination, blur, scale, and rotation. Six kinds of vehicle logo training set are formed using 25 images in average and the rest images are used to form the testing set. The Logo Recognition system that we programmed indicates a high recognition rate of the same kind of query images through adjusting different parameters.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

2418-2421

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.2418

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Online since:

December 2012

Authors:

Sheng Ke Wang*, Lili Liu, Xiaowei Xu

Keywords:

Feature-Matching, Query Image, SIFT, SURF, Train Images, Vehicle

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* - Corresponding Author

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