From Event: SPIE Optical Engineering + Applications, 2016
This paper deals with implementing a new algorithm for edge detection based on the Phase Stretch Transform (PST) for purposes of car plate license recognition. In PST edge detection algorithm, the image is first filtered with a spatial kernel followed by application of a nonlinear frequency-dependent phase. The output of the transform is the phase in the spatial domain. The main step is the 2-D phase function which is typically applied in the frequency domain. The amount of phase applied to the image is frequency dependent with higher amount of phase applied to higher frequency features of the image. Since sharp transitions, such as edges and corners, contain higher frequencies, PST emphasizes the edge information. Features can be further enhanced by applying thresholding and morphological operations.
Here we investigate the influence of noise and blur on the ability to recognize the characters in the plate license, by comparison of our suggested algorithm with the well known Canny algorithm.
We use several types of noise distributions among them, Gaussian noise, salt and paper noise and uniform distributed noise, with several levels of noise variances. The simulated blur is related to the car velocity and we applied several filters representing different velocities of the car.
Another interesting degradation that we intend to investigate is the cases that Laser shield license plate cover is used to distort the image taken by the authorities.
Our comparison results are presented in terms of True positive, False positive and False negative probabilities.
Hossein Asghari, Ofer Hadar, and Bahram Jalali, "Application of phase stretch transform to plate license identification under blur and noise conditions
(Conference Presentation)," Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997111 (Presented at SPIE Optical Engineering + Applications: August 31, 2016; Published: 2 November 2016); https://doi.org/10.1117/12.2237422.5178519712001.
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