Advancing Vehicle Logo Detection with DETRto Handle Small Logos and Low-Quality Images

Advancing Vehicle Logo Detection with DETRto Handle Small Logos and Low-Quality Images

detection transformers; logo; object detection; vehicle

Image-based vehicle logo detection is an important component in the implementation of vehicle information recognition technology, which supports the development of intelligent transportation systems. Vehicle logos, as elements that represent the identities of vehicle brands and models, play a significant role in completing vehicle identity data. The information obtained from this logo can be utilized to solve various traffic problems, such as vehicle document counterfeiting and theft, and for better traffic planning and management purposes. However, the main challenge in developing an accurate logo detection system lies in the wide variety of shapes, sizes, and positions of logos in different types of vehicles. In addition, the generally small size of logos, especially on certain vehicles, often makes it difficult for computer-based detection systems to recognize logos consistently, thus affecting the overall performance of the detection model. In this research, the Detection Transformers (DETR) method is used to build a vehicle logo detection system that focuses on small-scale logo. The testing process was conducted using the VL-10 dataset, which was specifically designed forvehicle logo detection evaluation. The results show that the DETR model can detect vehicle logos very well, even for small-scale logos. The model achieved an AP50 value of 0.952, which indicates a high level of accuracy and reliability in detecting the vehicle logo in the dataset used.

Rifky Fahrizal Ubaidillah1, Mahmud Dwi Sulistiyo2*, Gamma Kosala3, Ema Rachmawati4, Deny Haryadi5

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6236/1111

School of Computing, Telkom University, Bandung, Indonesia

August 17. 2025

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