A New Parametric Kernel Estimation Technique for License Plate Image De-blurring
A recognizable license plate in a picture taken by a traffic monitoring system is crucial for identifying the vehicles involved in traffic violations. In the image of a vehicle taken by a surveillance camera, the license plate is often blurred due to fast motion and cannot be recognized by the human eye. In this type of blurring, the blur kernel can be seen to be a linear uniform convolution parametrically described by its angle and length. In this paper, we introduce a new estimation technique to determine this kernel accurately in order to improve our de-blurred result. We use the Hough transform in estimating the direction in which the image is blurred. To determine the extent of the blur in that direction, we employ a new method involving the cepstrum of the blurred image. We compare the performance of our method to that of other recent blind de-blurring techniques. These comparisons show that our proposed scheme can handle significant blur in the captured image to give a good output image.
KeywordsMotion kernel Blur angle Blur length Hough transform Cepstral transform Point spread function Optical transfer function Ground truth Blind image de-blurring
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