Izvorni znanstveni članak
https://doi.org/10.17559/TV-20150901133605
Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons
Tomislav Keser
orcid.org/0000-0001-7300-0659
; J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Cara Hadrijana 10b, 31000 Osijek, Croatia
Ivan Dejanović
; J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Cara Hadrijana 10b, 31000 Osijek, Croatia
Sažetak
This article addresses the issue of traffic sign recognition. It contributes to a growing body of research done by the automotive industry due to a necessity for ensuring better safety on the roads. This paper presents a novel method for traffic signs recognition. The implementation of the whole process of traffic sign recognition has a step-wise nature but the novelty is introduced into the traffic sign shape detection stage. The method is based on a new approach for traffic sign shape recognition based on the image content occupancy analysis. Further, the traffic sign content classification is based on a simplistic relational correlation analysis. The tests were performed on image data comprising various roads and lighting conditions. The test includes different sizes of templates used in the correlation comparison method. The results are presented in a manner of successfulness of the correct recognition.
Ključne riječi
correlation comparison; image analysis; occupancy analysis; traffic sign detection; traffic sign recognition
Hrčak ID:
200594
URI
Datum izdavanja:
26.5.2018.
Posjeta: 1.776 *