Weather Eye: Object Detection in Adverse Weather Conditions

DOI

10.2991/978-94-6239-693-7_73How to use a DOI?

Keywords

Object Detection; Image Dehazing; Adverse Weather Vision; Deep Learning; YOLO; Visibility Enhancement

Abstract

Object detection systems used in outdoor settings are often degraded by adverse weather conditions, such as fog, haze and low illumination. Reduced visibility results in weak feature representation and unstable prediction and missed detections. This paper introduces Weather Eye, a weather aware object detection system to combine the image dehazing algorithm and real time deep learning object detection model. The proposed system works in two modes direct detection under clear conditions and enhancement assisted detection in case of degraded visibility. Classical and learning based dehazing methods which include Dark Channel Prior (DCP), CLAHE, DehazeNet, AOD-Net are applied prior to inference using a YOLO based detector. Experimental evaluation on real world outdoor data goes to show improvements in detection confidence, bounding box stability, as well as overall accuracy in comparison to direct detections on degradation images. The results prove that synchronization of visibility enhancement with object detection makes the system robust and reliable in dynamic outdoor lighting environments, which leads to diverse use cases for surveillance and traffic monitoring, and for safety playgrounds and safety critical applications.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Y. Mistica Dhas
AU  - K. Rohith
AU  - T. Gnanesh Reddy
PY  - 2026
DA  - 2026/06/16
TI  - Weather Eye: Object Detection in Adverse Weather Conditions
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 737
EP  - 743
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_73
DO  - 10.2991/978-94-6239-693-7_73
ID  - Dhas2026
ER  -