JOURNAL ARTICLE

Trademarks recognition based on local regions similarities

Abstract

This paper deals with content based image retrieval. We propose a logo recognition algorithm based on local regions, where the trademark (or logo) image is segmented by the clustering of points of interest obtained by Harris corners detector. The minimum rectangle surrounding each cluster is detected forming the regions of interest. Global features such as Hu moments and histograms of each local region are combined to find similar logos in the database. Similarity is measured based on the integrated minimum average distance of the individual components. The results obtained demonstrate tolerance to logos distortions such as rotation, occlusion and noise.

Keywords:
Artificial intelligence Rectangle Histogram Computer science Pattern recognition (psychology) Similarity (geometry) Trademark Computer vision Cluster analysis Noise (video) Rotation (mathematics) Image (mathematics) Mathematics

Metrics

4
Cited By
0.00
FWCI (Field Weighted Citation Impact)
13
Refs
0.19
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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