NDLI: Mutation detection system for actualizing traffic sign inventories

Content Provider	IEEE Xplore Digital Library
Author	Hazelhoff, Lykele Creusen, Ivo With, Peter H. N. de
Copyright Year	2014
Description	Author affiliation: CycloMedia Technology B.V, Zaltbommel, The Netherlands (Hazelhoff, Lykele; Creusen, Ivo; With, Peter H. N. de)
Abstract	Road safety is influenced by the adequate placement of traffic signs. As the visibility of road signs degrades over time due to e.g. aging, vandalism or vegetation coverage, sign maintenance is required to preserve a high road safety. This is commonly performed based on inventories of traffic signs, which should be conducted periodically, as road situations may change and the visibility of signs degrades over time. These inventories are created efficiently from street-level images by (semi-)automatic road sign recognition systems, employing computer vision techniques for sign detection and classification. Instead of periodically repeating the complete surveying process, these automated sign recognition systems enable re-identification of the previously found signs. This results in the highlighting of changed situations, enabling specific manual validation of these cases. This paper presents a mutation detection approach for semi-automatic updating of traffic sign inventories, together with a case study to assess the practical usability of such an approach. Our system re-identifies 94.8% of the unchanged signs, thereby resulting in a significant reduction of the manual effort required for the semi-automated actualization of the inventory. As the amount of changes equals to 16.9% of the already existing signs, this study also clearly shows the economic relevance and usefulness of periodic updating road sign surveys.
Starting Page	705
Ending Page	713
File Size	7841846
Page Count	9
File Format	PDF
ISBN	9789897581335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-05
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	SCITEPRESS
Subject Keyword	Histograms Mutation Detection Object Detection Three-dimensional displays Image color analysis Detectors Road safety Traffic Sign Recognition Object Classification Vehicles
Content Type	Text
Resource Type	Article

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