Performance evaluation for feature extractors on street view images

GÜZEL M. S.

IMAGING SCIENCE JOURNAL, cilt.64, sa.1, ss.26-33, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 64 Sayı: 1
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1080/13682199.2015.1109783
  • Dergi Adı: IMAGING SCIENCE JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.26-33
  • Anahtar Kelimeler: Feature extractor, Feature detector and descriptor, Hybrid architecture, Street view images, Image matching, CORNER DETECTION, HOUGH TRANSFORM, RECOGNITION
  • Ankara Üniversitesi Adresli: Evet

Özet

This paper comprises a comprehensive evaluation of popular feature extractor algorithms used in the analysis of street view images. Feature extractors are considered to consist of two main parts, namely, feature detectors and feature descriptors. This study aims to evaluate state-of-the-art feature extractors under different experimental conditions. Hybrid algorithms generated from current feature detectors and descriptors are tested under the same experimental conditions. The expected outcome of the experimental procedures should facilitate the selection of distinctive and robust extractors for different viewing conditions.