Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 942025

Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons


Keser, Tomislav; Dejanović, Ivan
Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons // Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 25 (2018), Supplement 1; 23-31 doi:10.17559/TV-20150901133605 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 942025 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons

Autori
Keser, Tomislav ; Dejanović, Ivan

Izvornik
Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku (1330-3651) 25 (2018), Supplement 1; 23-31

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
correlation comparison ; image analysis ; occupancy analysis ; traffic sign detection ; traffic sign recognition

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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Tomislav Keser (autor)

Citiraj ovu publikaciju

Keser, Tomislav; Dejanović, Ivan
Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons // Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 25 (2018), Supplement 1; 23-31 doi:10.17559/TV-20150901133605 (međunarodna recenzija, članak, znanstveni)
Keser, T. & Dejanović, I. (2018) Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons. Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 25 (Supplement 1), 23-31 doi:10.17559/TV-20150901133605.
@article{article, year = {2018}, pages = {23-31}, DOI = {10.17559/TV-20150901133605}, keywords = {correlation comparison, image analysis, occupancy analysis, traffic sign detection, traffic sign recognition}, journal = {Tehni\v{c}ki vjesnik : znanstveno-stru\v{c}ni \v{c}asopis tehni\v{c}kih fakulteta Sveu\v{c}ili\v{s}ta u Osijeku}, doi = {10.17559/TV-20150901133605}, volume = {25}, number = {Supplement 1}, issn = {1330-3651}, title = {Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons}, keyword = {correlation comparison, image analysis, occupancy analysis, traffic sign detection, traffic sign recognition} }
@article{article, year = {2018}, pages = {23-31}, DOI = {10.17559/TV-20150901133605}, keywords = {correlation comparison, image analysis, occupancy analysis, traffic sign detection, traffic sign recognition}, journal = {Tehni\v{c}ki vjesnik : znanstveno-stru\v{c}ni \v{c}asopis tehni\v{c}kih fakulteta Sveu\v{c}ili\v{s}ta u Osijeku}, doi = {10.17559/TV-20150901133605}, volume = {25}, number = {Supplement 1}, issn = {1330-3651}, title = {Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons}, keyword = {correlation comparison, image analysis, occupancy analysis, traffic sign detection, traffic sign recognition} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font