Hierarchy-of-Visual-Words: a Learning-based Approach for Trademark Image Retrieval

• Vítor Lourenço Federal Fluminense University
• Gabriela Silva Federal Fluminense University
• Leandro A. F. Fernandes Federal Fluminense University

DOI: https://doi.org/10.5753/sibgrapi.2019.9803

Resumo

We present the Hierarchy-of-Visual-Words (HoVW), a novel trademark image retrieval (TIR) method that decomposes images into simpler geometric shapes and defines a descriptor for binary trademark image representation by encoding the hierarchical arrangement of component shapes. The proposed hierarchical organization of visual data stores each component shape as a visual word. It is capable of representing the geometry of individual elements and the topology of the trademark image, making the descriptor robust against linear as well as to some level of nonlinear transformation. Experiments show that HoVW outperforms previous TIR methods on the MPEG-7 CE-1 and MPEG-7 CE-2 image databases.

Palavras-chave: Trademark Image Retrieval, Machine Learning, visual feature extraction and matching

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