NDLI: Improved raindrop detection using combined shape and saliency descriptors with scene context isolation

Content Provider	IEEE Xplore Digital Library
Author	Webster, D.D. Breckon, T.P.
Copyright Year	2015
Description	Author affiliation: Durham Univ., Durham, UK (Breckon, T.P.) \|\| Cranfield Univ., Cranfield, UK (Webster, D.D.)
Abstract	The presence of raindrop induced image distortion has a significant negative impact on the performance of a wide range of all-weather visual sensing applications including within the increasingly import contexts of visual surveillance and vehicle autonomy. A key part of this problem is robust raindrop detection such that the potential for performance degradation in effected image regions can be identified. Here we address the problem of raindrop detection in colour video imagery using an extended feature descriptor comprising localised shape, saliency and texture information isolated from the overall scene context. This is verified within a bag of visual words feature encoding framework using Support Vector Machine and Random Forest classification to achieve notable 86% detection accuracy with minimal false positives compared to prior work. Our approach is evaluated under a range of environmental conditions typical of all-weather automotive visual sensing applications.
Starting Page	4376
Ending Page	4380
File Size	1102842
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351633
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Image color analysis Feature extraction Context Visualization Support vector machines Radio frequency automotive vision rain detection raindrop distortion all-weather computer vision
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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