Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Recognition of Car Manufacturers using Faster R-CNN and Perspective Transformation

  • Ansari, Israfil (Department of Computer Eng., Andong National University) ;
  • Lee, Yeunghak (Department of Computer Eng., Andong National University) ;
  • Jeong, Yunju (School of Computer Science and Eng., Kyungpook National University) ;
  • Shim, Jaechang (Department of Computer Eng., Andong National University)
  • Received : 2017.07.13
  • Accepted : 2018.08.21
  • Published : 2018.08.31
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Abstract

In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.

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References

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