Title of article
Using Mean Shift for Iranian license plate detection
Author/Authors
Zandian, Mohtaram Department of Electrical Engineering - South Tehran Branch - Islamic Azad University, Tehran , Ghofrani, Sedigheh Department of Electrical Engineering - South Tehran Branch - Islamic Azad University, Tehran
Pages
16
From page
57
To page
72
Abstract
In this paper, Mean Shift (MS) as a clustering algorithm is used to localize the Iranian license plate. In this procedure after clustering, based on the optimized MS method, we applied the geometrical features and edge density in order to remove those parts in every cluster, which cannot be the license plate. The main advantages of MS are no need to know the number of clusters and it is completely independent of the Iranian license plate characters colors or background colors. However, for MS implementation, we should only predetermine a parameter named bandwidth. The experimental results show that our proposed method achieves appropriate performance. We should mention that our system accuracy for optical (OP) with 300 images is 94.6% and for infrared (IR) with 80 images is 98.3%.
Keywords
Mean Shift , Iranian License Plate Detection , Cluster Analysis , Kernel Density Estimator
Journal title
Astroparticle Physics
Serial Year
2019
Record number
2433004
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