2018
DOI: 10.1109/tcsvt.2017.2713806
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Riesz Fractional Based Model for Enhancing License Plate Detection and Recognition

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Cited by 79 publications
(56 citation statements)
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“…Many different procedures for number plate detection and extraction have been recently proposed, such as the fuzzified Gabor filter [1], the method based on the wavelet transform [11], attribute filtering [12], edge detection and noise reduction [13], and mathematical morphology [14]. Each of these approaches has its own limitations and advantages [15], [16], [17]. The quality of the cropped license plates resulting from these procedures is primarily influenced by the quality of the camera that captures the source image and by the quality of the algorithm used for the image processing.…”
Section: Recent Workmentioning
confidence: 99%
“…Many different procedures for number plate detection and extraction have been recently proposed, such as the fuzzified Gabor filter [1], the method based on the wavelet transform [11], attribute filtering [12], edge detection and noise reduction [13], and mathematical morphology [14]. Each of these approaches has its own limitations and advantages [15], [16], [17]. The quality of the cropped license plates resulting from these procedures is primarily influenced by the quality of the camera that captures the source image and by the quality of the algorithm used for the image processing.…”
Section: Recent Workmentioning
confidence: 99%
“…The artificial neural network [12,[26][27][28] is another very popular approach that has been used widely to recognize the license plate characters as well as many other classification tasks. The SVM classifier [13,16,29,30] with various feature extraction methods is also used to perform recognition tasks as SVM is strong and fast classifier for real time applications. The extreme learning machines (ELMs) [31] and hidden Markov model (HMM) [32] are also used as license plate recognition classifiers.…”
Section: Related Workmentioning
confidence: 99%
“…A modern mathematical model based on Riesz fractional operator for enhancing details of edge information in License plate images to improve the performances of text detection and recognition methods have been introduced by K. S Raghunandan et al [11]. The proposed model executes convolution operation of Riesz fractional derivative over each input image by enhancing the edge robustness in it.…”
Section: International Journal Of Computer Applications (0975 -8887) mentioning
confidence: 99%
“…Two decades has been exhausted for improving LPR systems harmonious to situations but there are still several challenges in achieving high detection and recognition rates. One such factor is low quality inclined by the following reasons: (i) sarcastic outdoor brightness conditions during image acquirement such as effects from headlight and sunshine, (ii) Low quality license plate images which often hold damaged or stained license plates and nonlicense plate characters printed on vehicles, and (iii) Perspective distortions due to distance or standpoint variations [11].…”
Section: Introductionmentioning
confidence: 99%