Suspected vehicle detection for driving without license plate using symmelets and edge connectivity

Jun-Wei Hsieh*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor into a symmetrical one without adding any time complexity. Then, different symmelets can be very efficiently extracted from road scenes. The set of symmelets can be then used to locate the desired vehicle's ROI using a projection technique. To examine whether a license plate exists within this ROI, an edge connectivity scheme is then proposed to highlight possible character regions for plate detection. This SVD system provides two advantages; there is no need of background subtraction and it is extremely efficient for real-time ITS applications without using any GPU.

Original languageEnglish
Title of host publication2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538629390
DOIs
StatePublished - 20 Oct 2017
Event14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 - Lecce, Italy
Duration: 29 Aug 20171 Sep 2017

Publication series

Name2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017

Conference

Conference14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
Country/TerritoryItaly
CityLecce
Period29/08/171/09/17

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