Methods for Identification and Vectorization of Traffic Elements from Orthographic Images

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F25%3A00386022" target="_blank" >RIV/68407700:21260/25:00386022 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.trpro.2025.10.039" target="_blank" >https://doi.org/10.1016/j.trpro.2025.10.039</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.trpro.2025.10.039" target="_blank" >10.1016/j.trpro.2025.10.039</a>

Result language

angličtina

Original language name

Methods for Identification and Vectorization of Traffic Elements from Orthographic Images

Original language description

Image documentation, particularly orthographic images, is a common and important foundation in traffic engineering, primarily used for mapping the evaluated location and displaying its spatial layout. The use of these images is also suitable as a base layer in graphic software. When subsequent work involves maintaining the current state or performing only partial reconstructions of the traffic space, the creator is required to reconstruct the existing condition. Design proposals in the form of studies are then based on reconstructing the traffic area from the current image. On raster images, manual tracing of elements such as road boundaries, horizontal traffic markings, or other features is typically performed, which are then vectorized into curves. If the area is complex within its existing layout, the designer often spends excessive time on vectorizing selected elements within the image. The aim of this article is to present methods for automating and processing image data that enable fast and efficient vectorization of selected traffic infrastructure elements. The intention was to develop a universal solution that does not rely on sophisticated machine learning systems, but instead emphasizes a step-by-step processing pipeline that is fully transparent and can be precisely controlled or customized by the user. As part of the study, the proposed automated method was compared with manual vectorization in terms of time efficiency. The results showed that automation can accelerate the process by approximately more than 2 times.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20104 - Transport engineering

Project

<a href="/en/project/EH23_021%2F0009003" target="_blank" >EH23_021/0009003: SimulUK - Simulation environment in the Ústí nad Labem Region</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Transportation Research Procedia

ISBN

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ISSN

2352-1457

e-ISSN

2352-1465

Number of pages

8

Pages from-to

297-304

Publisher name

Elsevier B.V.

Place of publication

Amsterdam

Event location

Zagreb

Event date

Dec 11, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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