@string{ispa="Proceedings of International Symposium on Image and Signal Processing and Analysis"}
@INPROCEEDINGS{VarjasTanacs_2013_ISPA, 
  AUTHOR = {Viktor Varjas and Attila Tanacs},
  BOOKTITLE = ispa,
  TITLE = {Car Recognition from Frontal Images in Mobile Environment},
  YEAR = {2013},
  ADDRESS = {Trieste, Italy},
  EDITOR = {G. Ramponi and S. Loncaric and A. Carini and K. Egiazarian},
  MONTH = {September},
  PAGES = {812-816},
  PUBLISHER = {IEEE},
  ABSTRACT = {Recognition of car make and model from frontal
    images is a common problem in computer vision. We refined
    existing approaches based on ROIs defined relative to the number
    plate. Square-Mapped-Gradient features are extracted from the
    ROI and recognition is accomplished by classification utilizing a
    learning set. The classifier is evaluated using ground truth data
    provided manually. Via numerical simulations we evaluated the
    detection tolerance of the method and proposed semi-automatic
    and fully automatic methods. The SMG-based classification is
    able to give nearly perfect results when there is no outlier class,
    which decreases to 92\% and 87\% in case of the semi-automatic
    and fully automatic methods, respectively. Separation between
    outliers and known types can be balanced by a threshold. Since
    the size of the learning set can be kept low and the size of the
    SMG features are small, this approach can be successfully used
    to solve mobile client-server scenarios.},
  note =	 {ISBN 978-953-184-187-0},
	pdf = {publications/ISPA2013.pdf}
}