License Plate Location Method Research Articles

Research on License Plate Location Algorithm Based on YOLOv5

License plate location is a key part of license plate recognition, and its positioning accuracy seriously determines the final result of license plate recognition. Firstly, the traditional license plate location methods are compared and analyzed. Secondly, in order to solve the localization problem in low resolution and multi-vehicle environment, a license plate method based on YOLOv5s was proposed by using deep learning image recognition technology, and data enhancement was introduced to improve YOLOv5s. Finally, the YOLOv5 algorithm is applied to real vehicle images under complex environmental conditions for experimental verification, and the results show that the accuracy is 99.12%. The experimental results show that the license plate location model based on YOLOv5S can effectively solve the influence of illumination, image quality and other factors on license plate location, improve the efficiency and accuracy compared with the traditional license plate location method, the algorithm has good robustness and fast calculation speed.

Research on the Algorithm of Locating and Cutting in License Plate Character Extraction

To improve the real-time and accuracy of intelligent vehicle character recognition algorithm, this paper mainly studies a new method for license plate location and character cutting: license plate location is carried out by combining HSV color space recognition with Sobel edge detection. The outer rectangle of the outermost contour of the character is used to judge the character boundary and segment the character. First, the original picture is converted to the HSV space, then the color information of the license plate is combined with the edge information to locate the license plate roughly, and finally the specific position of the license plate is determined according to the aspect ratio of the license plate. The location of the license plate is extracted for character segmentation preprocessing. Then, by traversing, the contour which meets the aspect ratio condition is found and the corresponding circumscribed rectangle is taken. The coordinate information of the rectangle is extracted and stored as a matrix, which is the basis of character segmentation. It is proved that this method has better accuracy and reliability than the traditional methods.

A Method of License Plate Location and Character Recognition based on CNN

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years，the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

New approach to vehicle license plate location based on new model YOLO‐L and plate pre‐identification

Currently, the conventional license plate location method fails to detect the license plate under complex road environments such as severe weather conditions and viewpoint changes. Besides, it is difficult for license plate location method based on machine learning to precisely locate the area of license plate. Moreover, license plate location method may incorrectly detect similar objects such as billboards and road signs as license plates. To alleviate these problems, this article proposes a new approach to vehicle license plate location based on new model YOLO-L and plate pre-identification. The new model improves in two aspects to precisely locate the area of license plate. First, it uses k-means++ clustering algorithm to select the best number and size of plate candidate boxes. Second, it modifies the structure and depth of YOLOv2 model. Plate pre-identification algorithm can effectively distinguish license plates from similar objects. The experimental results show that authors' proposed method not only achieves a precision of 98.86% and a recall of 98.86%, which outperforms the existing methods, but also has high efficiency in real time.

License Plate Recognition System Design

The license plate recognition system is an important part of modern traffic management. application which is very extensive. In this paper, a method to achieve three main modules split from the image pre-processing, license plate location and character. Image pre-processing module of this article is to image gray and step by Roberts operator edge detection. License plate positioning and segmentation using mathematical morphology is used to determine the license plate location method, and then use the license plate color information of color segmentation method to complete the license plate parts division. This article is to research its main part and use MATLAB to do the image processing simulation.

Research of License Plate Recognition System Based on Labview

The vehicle license plate recognition system is the intelligent traffic management system based on the image and the character recognition technology, which is an important part of the intelligent transportation system. This paper introduces a method of vehicle license plate location based on edge detection and morphological operations, virtual instrument is combined with machine vision of the license plate recognition method [1]. Finally the license plate number of the vehicle is get. Experiment results show that such method can simplify the algorithm and has some correct location rate.

Chinese License Plate Localization in Multi-Lane with Complex Background Based on Concomitant Colors

Color is an important feature of the Chinese license plate. In this paper, a license plate location method totally based on color information for the most common blue and yellow plates is proposed. First, use a special way to generate a grayscale image, highlighting the blue and yellow regions of the original image. Then by using the color concomitant property and transitions between the background and the characters, fake plates are removed, and real plates reserved. Finally, use the color information again to get a more accurate location result and remove the fake plates by using the relationship between the stroke width and the character size. The proposed method adopts two kinds of threshold methods: global threshold method and adaptive block threshold method. By automatically judging the illumination distribution of an image, the algorithm can decide which to use. The proposed method can be used to locate license plates in multi-lane with complex background, and works well even on images with uneven illumination. 2207 images from different traffic videos are used to do experiments, including 1314 images of daytime and 893 images of nighttime. Each image contains 0-7 plates, and the location rate achieves 95.01%.

A novel license plate location method based on wavelet transform and EMD analysis

Although various license plate location methods have been proposed in the past decades, their accuracy and ability to deal with different types of license plates still need to be improved. A robust license plate location method can raise the accuracy of the whole license plate recognition procedure. This paper proposes a robust method based on wavelet transform and empirical mode decomposition (EMD) analysis to search for the location of a license plate in an image to deal with some challenging problems in practice such as illumination changes, complex background and perspective change. By applying wavelet transform on a vehicle image and projecting the acquired details of the image, a wave crest that indicates the license plate will be generated. In order to locate the desired wave crest in the nonlinear and non-stationary projection dataset, EMD analysis is applied. Using the reconstructed projection data and the Hilbert transform of intrinsic mode function components, the position of the license plate is detected. Comprehensive experiments show that this method can locate the positions of various types of license plates with a high accuracy of 97.91% and a relatively short running time.

Method of License Plate Location Based on Mathematical Morphology and Color Characteristics

According to restrictions existing in the application of single license plate location algorithm in complicated background. A license plate location algorithm based on mathematical morphology and color characteristics is proposed. Firstly, the new method uses Ostu algorithm to select an optimal threshold, and according to the threshold carries on binary processing, then by using a new method of mathematical morphology for image edge detection. Finally combined mathematical morphology with color characteristic to locate license plate .Experiments show that this new method with higher accuracy and fewer restrictions on background is superior to traditional or a single method and can be widely used.

A Real-Time Method for License Plate Location

License plate location is the first and crucial stage in license plate recognition. Although many license plate location methods achieve higher success rate, they are always time-consuming. However, robust real-time characteristic is important to application of license plate recognition. In this paper, a texture-based method of license plate location is proposed to enhance real-time characteristic while keeping higher success rate. It consists of three parts: preprocessing, region of interested (ROI) location and ROI filtration. Experimental has demonstrated that the proposed method achieve average execution time of 49ms and success rate of 96.3% simultaneously.

A Vehicle License Plate Location Method Based on the Mixed Programming between VC++ and Matlab

The location of vehicle license plate is the important component of realization intelligent traffic system.While programming locaton of car license plate.Visual C++ language,a software development platform,is widely used.Matlab Compiler language is simple and easy to use and has strong ability of Graphics processing. Accordingly ,This paper presents a new method based on the Visual C++ and Matlab mixed programming of image processing,Image processing for vehicle license plate. And introduced the way to achieve application of this method in the image processing.Experimental evidence,this method has great application value.

A Novel and Fast Method for Precise License Plate Location from Digital Images Based on Fusion of Salient Features

A Novel and Fast Method for Precise License Plate Location from Digital Images Based on Fusion of Salient Features

Persian Vehicle License Plate Recognition Using Multiclass Adaboost

Des pite the success of License Plate Recognition (LPR) methods in the past decades, this problem is quite a challenge due to the diversity of plate formats and multiform outdoor illumination conditions during image acquisition. This paper presents a real-time and robust method for Persian license plate location and recognition. The proposed method consists of four main steps namely (I) Plate localization (II) Normalization, (III) Character segmentation, and (IV) Optical character recognition. First, all plates of the grabbed image are located rapidly and accurately using morphological operation and AdaBoost. After that, plates are normalized, and if they are skewed, then they will be aligned. In next step, convolution of each plate and a predefined binary mask is calculated, and then characters are segmented based on the obtained information. Finally, SAMME is utilized to classify extracted Persian numbers, alphabets, and words. In comparison with other methods, this system achieves high accuracy in plate localization, segmentation, and recognition. The success rate of the proposed method is 96.93% for plate localization utilizing morphological operation and AdaBoost, 98.75% for character segmentation, and 94.5% for optical character recognition utilizing SAMME. Finally, the overall accuracy of the proposed method is examined 90.45%.

Research on an Efficient Method of License Plate Location

Abstract In the application of intelligent transportation system (ITS), license plate (LP) location is one of the most crucial step. In view of illumination variance, noise, complex and dirty background, this paper presents a license plate location method, which based on edge information analysis with a preprocessing technique. License plate area contains rich edge and texture information, which can be used to detect a number plate location. Experimental results demonstrated the great robustness and efficiency of our method.

An Improved License Plate Location Method Based On Edge Detection

License plate location as one of the key steps in license plate recognition system, the positioning accuracy is direct impact on the effect of license plate recognition. In this paper, for the plate image that is under different backgrounds and lighting conditions,a license plate location method based on an improved prewitt arithmetic operator was proposed. Firstly,do improved prewitt operation on the preprocessed plate image. Then, use the characteristics of vehicle license, adopt the horizontal and vertical projection method to determine the location of the upper and lower edge around the edge position, in order to achieve the positioning of vehicle license. The experiments results show that the algorithm with high accuracy, positioning speed and have good practical value.

License Plate Location Method Based on LOG Edge Detection Operator

The license plate location method is the key technology of license plate recognition system, new algorithm is proposed based on LOG operator detecting edge of License Plate Location. First, a large number of color plate images are preprocessed to remove the background interference information, and then rough location of license plate based on block method, search area of plate will be greatly reduced and accurate positioning the plate will be realized by LOG operator combined with projection method. Static license plate image positioning by simulation and analysis show that the method has high accuracy in license plate location.

An Improved Method for Vietnam License Plate Location based on Mathematic Morphology and Measuring Properties of Image Regions

In the Automatic License Plate Recognition (ALPR) system, the License Plate Location (LPL) is the key step before the final recognition. This paper proposed an improved LPL algorithm for Vietnam vehicle license plates (LP). The proposed algorithm consists of three main modules: Pre-processing (convert RGB image to grayscale image, adjust grayscale image intensity, image binarization use Otsu method), LP candidates location (morphology opening to remove noises & dilation operation, measure properties of image regions to find candidates), LP exactly location (finding the LP angle & rotating LP, cut exactly LP region). We implemented test for 350 Vietnam vehicle images, which obtained from the actual system, the average rate of accuracy of our method is 98.64%, our results are more exactly presented methods.

License Plate Location Algorithm Based on Twin SVM

A method for license plate location based on Twin SVM is proposed in this paper. Firstly, the mathematical models of Twin SVM are introduced, and then the feature extractions of license plate image are discussed, finally it is proved that this location method is very precise and efficient by experiments in VC development environment.

A Method of License Plate Location Based on Gray Images and Binary Images

The fast location is especially important, in the license plate recognition. In this paper, we received the candidate regions by the mathematical morphological operation, and then scanned the middle line of the binarized candidate areas. Determine the plate region using the black-white variations of the pixel in this middle line. This method is based on single line scanning which can reduce the computation time and improve the speed of license plate location.

Research on the segmentation of license plate characters

A license plate location method based on plate texture and color is introduced. Connected domain method and template matching method are chosen to realize characters segmentation. Firstly, Canny edge detection and dilatation & erosion algorithm referred to morphological image processing are used to fuse the region with the similar texture features, and then color segmentation method is adopted with the fusion images to achieve plate location shearing. Secondly, characters segmentation is implemented with connected domain method. Finally, segmented characters are recognized with the template. Experiments show that the method is simple, easy and effective to carry out plate location and recognition.