Sparse-coding license plate character recognition method based on shape and contour features

A sparse coding and contour feature technology, applied in the field of sparse coding license plate character recognition, can solve the problem of low character recognition accuracy, and achieve the effects of efficient classification characteristics, good scalability, and a wide range of applications.

Inactive Publication Date: 2014-04-30
XIAN UNIV OF TECH
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Problems solved by technology

[0006] The purpose of the present invention is to provide a sparsely coded license plate character recognition meth

Method used

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  • Sparse-coding license plate character recognition method based on shape and contour features
  • Sparse-coding license plate character recognition method based on shape and contour features
  • Sparse-coding license plate character recognition method based on shape and contour features

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Embodiment Construction

[0048] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. Sparse coded license plate character recognition method based on shape contour features, such as figure 1 As shown, it consists of the learning process of the sparse dictionary (above the dotted line) and the recognition process of the sparse dictionary (below the dotted line).

[0049] 1. The learning process of the sparse dictionary specifically includes the following steps:

[0050] (1) Preprocessing the license plate image of the training sample to obtain the training character image set;

[0051] In order to consider the differences caused by factors such as license plate clarity, cleanliness, new and old background colors, and lighting background, ensure that enough training sample license plate pictures are collected, so that the number of each character in the training process is at least 100. License plate image preprocess...

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Abstract

The invention provides a sparse-coding license plate character recognition method based on shape and contour features. The method comprises a sparse dictionary learning process and a dictionary-utilizing character recognition process. The method mainly comprises the following steps: firstly, a training image set is formed by pre-processing standard license plate images; secondly, feature extraction is performed on the training image set, so that a training feature set is formed; thirdly, a sample region feature and a chain code histogram feature of the raining feature set are introduced into an objective function, sparse dictionary learning is performed on license plate character samples off line to obtain dictionaries corresponding to all characters, and a dictionary set is formed by all the dictionaries; fourthly, feature extraction is performed on test sample data; fifthly, test sample features are subjected to sparse representation in each dictionary, and license plate character recognition is performed through reconstruction errors. Since region features and boundary features of character images are considered at the same time, the sparse-coding license plate character recognition method is a fast and robust license plate character recognition method.

Description

technical field [0001] The invention belongs to the technical field of image processing and intelligent transportation, and in particular relates to a sparsely coded license plate character recognition method based on shape and contour features. Background technique [0002] License plate recognition is an important link in Intelligent Transportation System (ITS), which can be widely used in intersection monitoring, parking lot monitoring and management, highway toll collection and other occasions. License plate recognition consists of license plate location, license plate tilt correction, character segmentation and character recognition. License plate character recognition is an important factor affecting the system recognition rate based on the completion of the previous parts. [0003] Due to the low resolution of the character dot matrix in the license plate, the low resolution will lead to the loss of character feature information and cause the sticking of strokes. In...

Claims

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Application Information

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IPC IPC(8): G06K9/62
Inventor 赵凡廖开阳曲方莹张二虎
Owner XIAN UNIV OF TECH
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