Vehicle logo recognition using histograms of oriented gradient descriptor and sparsity score

Kittikhun Meethongjan, Thongchai Surinwarangkoon, Vinh Truong Hoang

Abstract


Most of vehicle have the similar structures and designs. It is extremely complicated and difficult to identify and classify vehicle brands based on their structure and shape. As we requirea quick and reliable response, so vehicle logos are an alternative method of determining the type of a vehicle. In this paper, we propose a method for vehicle logo recognition based on featureĀ  selection method in a hybrid way. Vehicle logo images are first characterized by histograms of oriented gradient descriptors and the final features vector are then applied feature selection method to reduce the irrelevant information. Moreover, we release a new benchmark dataset for vehicle logo recognition and retrieval task namely, VLR-40. The experimental results are evaluated on this database which show the efficiency of the proposed approach.

Keywords


feature selection; HOG descriptor; image classification; sparsity score; vehicle logo recognition;

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DOI: http://doi.org/10.12928/telkomnika.v18i6.16133

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TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
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