TRODO: A public vehicle odometers dataset for computer vision

Data in Brief

Burcu Yılmazel¹  Ali Yürekli²  Kaouther Mouheb³ 

[1] Department of Computer Engineering, Eskişehir Technical University, Eskişehir 26555, Turkey;Corresponding author.;Department of Computer Engineering, Eskişehir Technical University, Eskişehir 26555, Turkey;

关键词: Computer vision;    Image processing;    Digit recognition;    Odometer;    Mileage reading;   

DOI  :  

来源: DOAJ

【 摘 要 】

In the field of transportation and logistics, smart vision systems have been employed successfully to automate various tasks such as number-plate recognition and vehicle identity recognition. The development of such automated systems is possible with the availability of large image datasets having proper annotations. The TRODO dataset is a rich-annotated collection of odometer displays that can enable automatic mileage reading from raw images. Initially, the dataset consisted of 2613 frames captured in different conditions in terms of resolution, quality, illumination and vehicle type. After data pre-processing and cleaning, the number of images was reduced to 2389. The images were annotated using the CVAT image annotation tool. The dataset provides the following information for each frame: the type of odometer (analog or digital), the mileage value displayed on the odometer, the bounding boxes of the odometer, and the digits and characters displayed on the screen. Combined with machine learning and artificial intelligence, the TRODO dataset can be used to train odometer classifiers, digit recognition and number reading models from odometers and similar types of displays.

【 授权许可】

Unknown