2012
DOI: 10.5815/ijigsp.2012.12.02
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Implementation of a High Speed Technique for Character Segmentation of License Plate Based on Thresholding Algorithm

Abstract: This paper presents, complete step by step description design and implementation of a high speed technique for character segmentation of license plate based on thresholding algorithm. Because of vertical edges in the plate, fast Sobel edge detection has been used for extracting location of license plate, after stage edge detection the image is segmented by thresholding algorithm and the color of characters is changed to white and the color of background is black. Then, boundary's pixels of license plate are sc… Show more

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Cited by 4 publications
(2 citation statements)
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“…We can easily include extraneous pixels that aren't part of the desired region, and we can just as easily miss isolated pixels within the region (especially near the boundaries of the region). These effects get worse as the noise becomes worse, simply because it's more likely that a pixels intensity doesn't represent the normal intensity in the region [14]. When we use thresholding, we typically have to balance with the tradeoff, sometimes losing too much of the region or getting too many extraneous background pixels.…”
Section: A Prepossessing Stepmentioning
confidence: 98%
“…We can easily include extraneous pixels that aren't part of the desired region, and we can just as easily miss isolated pixels within the region (especially near the boundaries of the region). These effects get worse as the noise becomes worse, simply because it's more likely that a pixels intensity doesn't represent the normal intensity in the region [14]. When we use thresholding, we typically have to balance with the tradeoff, sometimes losing too much of the region or getting too many extraneous background pixels.…”
Section: A Prepossessing Stepmentioning
confidence: 98%
“…We can easily include irrelative pixels that aren't part of the desired region in real image we actually need, and we can easily miss isolated pixels within the region as well (especially near the boundaries of the region). These effects get increasingly worse as the type of noise becomes more and more complicated, simply because it's more likely that a pixel intensity cannot represent free-noise image intensity in the region [18]. When we use thresholding method, we typically have to balance with the tradeoff in terms of losing too much of the region informations and getting too many background pixels with noise.…”
Section: Prepossessing Stepmentioning
confidence: 99%