Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection Algorithm

04/11/2021
by   Vera Soboleva, et al.
0

Autonomous vehicles use cameras as one of the primary sources of information about the environment. Adverse weather conditions such as raindrops, snow, mud, and others, can lead to various image artifacts. Such artifacts significantly degrade the quality and reliability of the obtained visual data and can lead to accidents if they are not detected in time. This paper presents ongoing work on a new dataset for training and assessing vision algorithms' performance for different tasks of image artifacts detection on either camera lens or windshield. At the moment, we present a publicly available set of images containing $8190$ images, of which $3390$ contain raindrops. Images are annotated with the binary mask representing areas with raindrops. We demonstrate the applicability of the dataset in the problems of raindrops presence detection and raindrop region segmentation. To augment the data, we also propose an algorithm for data augmentation which allows the generation of synthetic raindrops on images. Apart from the dataset, we present a novel gradient-based algorithm for raindrop presence detection in a video sequence. The experimental evaluation proves that the algorithm reliably detects raindrops. Moreover, compared with the state-of-the-art cross-correlation-based algorithm \cite{Einecke2014}, the proposed algorithm showed a higher quality of raindrop presence detection and image processing speed, making it applicable for the self-check procedure of real autonomous systems. The dataset is available at \href{https://github.com/EvoCargo/RaindropsOnWindshield}{$github.com/EvoCargo/RaindropsOnWindshield$}.

READ FULL TEXT

page 1

page 3

page 4

research
10/12/2021

Robust Glare Detection: Review, Analysis, and Dataset Release

Sun Glare widely exists in the images captured by unmanned ground and ae...
research
12/04/2019

Let's Get Dirty: GAN Based Data Augmentation for Soiling and Adverse Weather Classification in Autonomous Driving

Cameras are getting more and more important in autonomous driving. Wide-...
research
05/01/2019

RRPN: Radar Region Proposal Network for Object Detection in Autonomous Vehicles

Region proposal algorithms play an important role in most state-of-the-a...
research
05/23/2023

Multi-Echo Denoising in Adverse Weather

Adverse weather can cause noise to light detection and ranging (LiDAR) d...
research
10/31/2022

Tree Detection and Diameter Estimation Based on Deep Learning

Tree perception is an essential building block toward autonomous forestr...
research
06/03/2022

CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather with a High-quality Real Snow Dataset

Snow is one of the toughest adverse weather conditions for object detect...
research
10/07/2022

Leveraging Structure from Motion to Localize Inaccessible Bus Stops

The detection of hazardous conditions near public transit stations is ne...

Please sign up or login with your details

Forgot password? Click here to reset