The Bangladesh road traffic sign dataset in real-world images for traffic sign recognition

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-03-27 DOI:10.1016/j.dib.2025.111523

Md. Ariful Islam, Dewan Md. Farid

引用次数: 0

Abstract

Traffic sign detection and classification have significant impacts in the field of automated driving system, traffic management, driver assistance system, to detect traffic rules violations etc. In this paper, we have presented the Bangladesh road traffic sign benchmark dataset, which consists of 10259 real-world traffic sign images captured from various locations in Bangladesh and 10259 annotated images. A Total of 31 distinct traffic sign images were collected including Crossroad, Emergency Stopping, Sharp left turn. For image annotation, a sophisticated tool, Roboflow, has been utilized and data augmentation techniques have been applied to enhance the diversity of the images. The dataset is useful for training and testing of any deep convolutional neural networks (CNNs) models for traffic sign recognition. The dataset is publicly accessible via the following link: https://zenodo.org/records/14969122.

查看原文本刊更多论文

交通标志检测和分类在自动驾驶系统、交通管理、驾驶员辅助系统、违反交通规则检测等领域具有重要影响。本文介绍了孟加拉国道路交通标志基准数据集，该数据集由从孟加拉国不同地点采集的 10259 幅真实交通标志图像和 10259 幅注释图像组成。共收集了 31 幅不同的交通标志图像，包括十字路口、紧急停车、左急转弯。在图像注释方面，使用了先进的工具 Roboflow 和数据增强技术，以提高图像的多样性。该数据集可用于训练和测试任何用于交通标志识别的深度卷积神经网络（CNN）模型。该数据集可通过以下链接公开访问：https://zenodo.org/records/14969122。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.