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http://dx.doi.org/10.33851/JMIS.2019.6.4.235

Vehicle Manufacturer Recognition using Deep Learning and Perspective Transformation  

Ansari, Israfil (Dept. Of Computer Engineering, Andong National University)
Shim, Jaechang (Dept. Of Computer Engineering, Andong National University)
Publication Information
Journal of Multimedia Information System / v.6, no.4, 2019 , pp. 235-238 More about this Journal
Abstract
In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.
Keywords
Vehicle Logo; Object detection; YOLO; Faster R-CNN; VMR;
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