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 feature 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.
Vehicle logo recognition using histograms of oriented gradient descriptor and sparsity score
2020-12-01
doi:10.12928/telkomnika.v18i6.16133
TELKOMNIKA (Telecommunication Computing Electronics and Control); Vol 18, No 6: December 2020; 3019-3025 ; 2302-9293 ; 1693-6930 ; 10.12928/telkomnika.v18i6
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Boosting histograms of descriptor distances for scalable multiclass specific scene recognition
British Library Online Contents | 2011
|British Library Online Contents | 2010
|Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme
Online Contents | 2010
|