NDLI: Vision-Based Nighttime Vehicle Detection Using CenSurE and SVM

Content Provider	IEEE Xplore Digital Library
Author	Kosaka, N. Ohashi, G.
Copyright Year	2000
Abstract	In this paper, we propose a method for detecting vehicles from a nighttime driving scene taken by an in-vehicle monocular camera. Since it is difficult to recognize the shape of the vehicles during nighttime, vehicle detection is based on the headlights and the taillights, which are bright areas of pixels called blobs. Many research studies using automatic multilevel thresholding are being conducted, but these methods are prone to get affected by the ambient light because it uses the luminance of the whole image to derive the thresholds. Owing to such reasons, we focused on the Laplacian of Gaussian operator, which derives the response of luminance difference between the blob and its surroundings. Compared with automatic multilevel thresholding, Laplacian of Gaussian operator is more robust to the ambient light. However, the computational cost to derive the response of this operator is large. Therefore, we used a method called Center Surround Extremas to detect the blobs in high speed. Since the detected blobs include nuisance lights, we had to determine whether the blob is a light of a vehicle or not. Thus, we classified them according to the features of the blob using support vector machines. Then, we detected vehicle traffic lane and specified the region where the vehicle may exist. Finally, we classified the blobs based on the movements across the frames. We applied the proposed method to nighttime driving sequences and confirmed the effectiveness of the classification process used in this method and that it could process within frame rate.
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	2599
Ending Page	2608
Page Count	10
File Size	1614417
File Format	PDF
ISSN	15249050
Volume Number	16
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Cameras Shape Image edge detection Support vector machines Vehicle detection Feature extraction Center Surround Extremas Intelligent transport systems nighttime driving scenes vehicle detection
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

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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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