Trafik Işığı Tespiti Yapan Bir Sürücü Güvenlik Destek Sistemi

Year 2018, Volume: 21 Issue: 2, 419 - 426, 01.06.2018

Çağlar Kılıkçıer Ersen Yılmaz

https://doi.org/10.2339/politeknik.389606

Abstract

Sürücü güvenlik destek sistemleri
(SGDS) sayesinde trafik kazası sayıları azaltılabilmektedir. Bu çalışmada,
trafik ışıklarını bularak sürücüyü uyaran bir sürücü güvenlik destek sistemi
önerilmiştir.  Önerilen SGDS sadece
görsel bilgilerle çalışmakta ve trafik ışığı tespiti yapmaktadır. Sistem ilk
olarak alınan imgeleri gri ölçekli imgelere dönüştürerek Otsu kriterine göre
çok seviyeli eşiklemeye tabi tutmaktadır. Eşiklenmiş olan imgeler için
sırasıyla bağlı bileşen analizi ve parça analizi yapılarak trafik ışığı
olabilecek ilgi duyulan bölgeler bulunmaktadır. Bulunan bu bölgelerden renk
bilgisini de içeren özellik vektörleri çıkartılmaktadır. Son olarak, Destek
Vektör Makinesi (DVM) ile ilgi duyulan bölgelerin trafik ışığı olup olmadığına
karar verilmektedir. Önerilen SGDS’nin başarımı şehir ortamından elde edilmiş
imgeler üzerinde incelenmiştir.  

Keywords

DVM, çok seviyeli eşikleme, pso, trafik ışığı

A Driver Safety Support System Which Detects Traffic Lights

Abstract

The number of traffic accidents can be decreased
through driver safety support systems (DSSS). In this study, a driver safety
support system is proposed in which the driver is warned by finding traffic
lights. The proposed DSSS works on only visual information and detects traffic
lights. The system primarily transforms the received images into gray scale
images and subject them to multi-level thresholding with Otsu criteria. The
regions of interest which can be traffic lights are found for the thresholded images
by using connected component analysis and blob analysis, respectively. Feature
vectors including the color information are extracted from the founded regions.
Finally, it is decided if the regions of interest are traffic lights by using
support vector machines (SVM). The performance of the proposed DSSS is examined
on the images obtained from urban areas.

Keywords

SVM, multi-level thresholding, pso, traffic light

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