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LPR (License Plate Recognition) is a foundation component of modern transportation management systems. It uses a set of computer image-processing technologies to identify vehicle by its license plate. Character recognition is the core of LPR, which is essentially a multi-classification problem. The challenge is how to recognize every character of the license plate accurately and rapidly in case of...
In this paper, a novel recognition method is proposed aiming at the current difficulties existing in Car License Plate Characters recognition. Firstly, the method builds three Template Libraries apart including Chinese characters, English letters and Figure. The character to be recognized is preprocessed involving normalization, refinement and so on. And then, it is identified by using modified Hausdorff...
In this article, BP network learning algorithm is improved by using momentum and genetic algorithm after analyzing the defects of the BP network learning algorithm. So the convergence rate of BP network is speeded up greatly. The vehicle license plate character image is segmented and feature is extracted by edge detection using sobel operator. And then license plates of cars are automatically recognized...
Qualitative criterion (QC) plays an important role in human recognition, judgment, memory and evaluation fields. During a study of character recognition, a series of concepts, such as qualitative criterion cluster (QCC), criterion skeleton code (CSC) and criterion skeleton (CS), based on the principle of granular computing are proposed in this paper. In addition, a novel method is also proposed to...
In this paper, we work mainly on character recognition. First, we decompose the plate characters by framelet and select the transform coefficients using wrapper method as the character features, then send them to BP neural network for recognition. With our method, the recognition rate of letter characters reaches 99.25%, the number characters reaches 99.3%, the results illustrate that our method is...
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