License plate recognition method based on Hidden Markov models

A hidden Markov, license plate recognition technology, applied in the field of license plate recognition, can solve problems such as poor accuracy of Chinese characters, achieve high accuracy and improve the effect of intelligent traffic management

Inactive Publication Date: 2014-12-10
XONLINK INC
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Problems solved by technology

The existing license plate recognition technology can accurately recognize English characters and

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  • License plate recognition method based on Hidden Markov models
  • License plate recognition method based on Hidden Markov models
  • License plate recognition method based on Hidden Markov models

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[0024] The present invention will be further described below in conjunction with the drawings.

[0025] Reference Figure 1 ~ Figure 3 , A method for license plate recognition based on a hidden Markov model, which detects vehicles on a monitored road and automatically extracts and processes vehicle license plate information. The license plate recognition method includes the following steps:

[0026] Step 1. License plate positioning. The video data of the monitoring equipment is decoded, and the data frames are separated to form the image data of each frame of video, so as to facilitate the subsequent identification of vehicle information on a single image.

[0027] The license plates captured are generally color images, and the license plates have black characters on a yellow background and white characters on a blue background. In order to process these license plate images together, the license plate must be grayed out first, and the image is converted into a grayscale image acc...

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Abstract

A license plate recognition method based on Hidden Markov models includes 1, license plate positioning; 2, character segmentation, namely performing binaryzation processing on images, and determining the character positions according to the height-width ratio of characters of Chinese license plates; 3, character recognition, namely applying decomposition rules on each Chinese character in a set in the process of Chinese character processing to generate progressive split graph including radicals as nodes, finding out the optimization problem of an optimal radical set representing the Chinese character set in a formulation manner through the maximum likelihood and minimum description length, solving the optimization problem to acquire the optimal radical set, and using the optimal radical set in the character recognition algorithm based on the Hidden Markov models; when phabetic and digital characters are processed, extracting character skeletal accumulation characteristics, including stroke slope accumulation characteristics, inflection point amplitude accumulation characteristics and contour depth accumulation characteristics, by scanning four sides of characters. The method has high automation level, and the Chinese character recognition accuracy rate is improved greatly.

Description

technical field [0001] The invention relates to a license plate recognition technology, in particular to a license plate recognition method. Background technique [0002] Vehicle License Plate Recognition (VLPR) is an application of computer video image recognition technology in vehicle license plate recognition. [0003] License plate recognition technology requires the ability to extract and recognize moving license plates from complex backgrounds, and identify vehicle license plates through license plate extraction, image preprocessing, feature extraction, and license plate character recognition. It can realize the functions of parking lot charge management, traffic flow control index measurement, vehicle positioning, car anti-theft, expressway overspeed automatic supervision, red light electronic police, road toll station and so on. It has practical significance for maintaining traffic safety and urban security, preventing traffic jams, and realizing intelligent traffic...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 张标标刘翔李仁旺吴斌宋海龙毛江雄陈跃鸣严易洲杜克林
Owner XONLINK INC
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