Vehicle License Plate Detector in Compressed Domain

Muhammet Sebul Beratoglu*, Behcet Ugur Toreyin

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

14 Atıf (Scopus)

Özet

Data compression techniques allow data size to be reduced prior to data transmission and involve decompression upon transfer. This study shows for the first time that license plate (LP) detection can be accomplished without full decompression of the encoded data. Therefore, by determining in advance which images are required for LP recognition, computational costs of the system can be reduced. The proposed approach is realized on High Efficiency Video Coding (HEVC) based compressed video sequences. Two methods are provided that generate images from HEVC attributes. Fully decoded pixel domain images are also generated for comparative purposes from the same encoded data. The YOLO V3 Tiny Object Detector is used in order to detect LPs in the generated images. EnglishLP, a public dataset, is used to interpret the findings in terms of speed and precision and for comparison with previous studies. An additional contribution of the paper is that a new compressed domain LP database has been created and made publicly available, comprising images captured by a commercial license plate recognition system. Using at least two-orders-of-magnitude less amount of data, the proposed compressed domain LP detector achieved similar precision and recall values to those of the state-of-the-art LP detection schemes tested on both datasets. Moreover, the proposed method results in more than 30% saving in inference time. The results suggest that the proposed method can be utilized for rapid video archive searching applications.

Orijinal dilİngilizce
Makale numarası9466149
Sayfa (başlangıç-bitiş)95087-95096
Sayfa sayısı10
DergiIEEE Access
Hacim9
DOI'lar
Yayın durumuYayınlandı - 2021

Bibliyografik not

Publisher Copyright:
© 2013 IEEE.

Finansman

This work was supported in part by the Scientific Research Projects Coordination Department (BAP), Istanbul Technical University, under Project ITU-BAP MGA-2017-40964, and in part by The Scientific and Technological Research Council of Turkey (TÜBİTAK) - TEYDEB under Grant 3190538.

FinansörlerFinansör numarası
TEYDEB3190538
TÜBİTAK
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Istanbul Teknik ÜniversitesiITU-BAP MGA-2017-40964

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