On circular traffic sign detection and recognition

KAPLAN BERKAYA S., GÜNDÜZ H., ÖZŞEN Ö., Akinlar C., GÜNAL S.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.48, ss.67-75, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.eswa.2015.11.018
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.67-75
  • Anahtar Kelimeler: Circular traffic sign detection, EDCircles, Traffic sign recognition, HOG, Gabor filter, LBP, LOCAL BINARY PATTERNS, CLASSIFICATION, SEGMENTATION, COLOR, MODEL
  • Anadolu Üniversitesi Adresli: Evet

Özet

Automatic traffic sign detection and recognition play crucial roles in several expert systems such as driver assistance and autonomous driving systems. In this work, novel approaches for circular traffic sign detection and recognition on color images are proposed. In traffic sign detection, a new approach, which utilizes a recently developed circle detection algorithm and an RGB-based color thresholding technique, is proposed. In traffic sign recognition, an ensemble of features including histogram of oriented gradients, local binary patterns and Gabor features are employed within a support vector machine classification framework. Performances of the proposed detection and recognition approaches are evaluated on German Traffic Sign Detection and Recognition Benchmark datasets, respectively. The results of the experimental work reveal that both approaches offer comparable or even better performances with respect to the best ones reported in the literature and are compatible to real-time operation as well. (C) 2015 Elsevier Ltd. All rights reserved.