Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF Neural Network

Shan, Baoming

doi:10.4304/jcp.6.2.246-253

Cited by 30 publications

(14 citation statements)

References 13 publications

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“…Table 2. Comparison among different types of recognition for Iraqi license plate System Total Recognition % Shihab [2] 97 Abbas [3] 98.245 Abed [4] 92 Tawfeeq [5] 93.33 Table 3.Comparison among different types of recognition for EU plate System Total Recognition % Janowski [10] 80 Li [11] 80 Zhu [12] 87.33 Sarfaz [13] 95 Donoser [14] 94 Abdulbaki [15] In [16][17][18][19][20][21][22][23][24][25][26][27] the license plate was projected vertically to define the boundaries of the characters, then horizontally to detect each character. One easily can recognize from Table 4 and above, that the process of segmentation in Iraq license plate should pass through three steps, first for Arabic characters, second for English characters, and third for car type, while in EU plate, only a single stage will needed.…”

Section: Figure 2 Proposal System For License Plate Recognition Systemmentioning

confidence: 99%

Comparative Study between Iraqi and EU Vehicles License Plates in view of Segmentation and Recognition

2019

JAUS

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License Plate Recognition (LPR) system uses license plates to recognize vehicles by using image processing technology. After increasing the implementations and applications on the vision of vehicles license plates around the world, the design of the plate became an important issue, and the information held by the plate should be selected properly to avoid redundancy and to improve the detection system performance. In Iraq, the new license plate was established in 2012. The goal of this paper is to evaluate the new Iraqi license plate by comparing it with that used in the European Union. The study compares them in terms of accuracy, performance and complexity. The evaluation shows that there are many redundancies and not useful regions in the Iraqi license plate that make the decision in the segmentation and recognition process more difficult. Keywords: characters segmentation; Iraqi license plate; license plate recognition (LPR); plate design; vehicle plate detection. RESUMEN/ El sistema de reconocimiento de matrículas (LPR) utiliza placas para reconocer vehículos mediante el uso de tecnología de procesamiento de imágenes. Después de aumentar las implementaciones y aplicaciones sobre la visión de las placas de vehículos en todo el mundo, el diseño de la placa se convirtió en un tema importante, y la información contenida en la placa debería seleccionarse adecuadamente para evitar la redundancia y mejorar el rendimiento del sistema de detección. En Iraq, la nueva matrícula se estableció en 2012. El objetivo de este documento es evaluar la nueva matrícula iraquí comparándola con la utilizada en la Unión Europea. El estudio los compara en términos de precisión, rendimiento y complejidad. La evaluación muestra que hay muchas redundancias y regiones no útiles en la matrícula iraquí que dificultan la decisión en el proceso de segmentación y reconocimiento. Palabras clave: segmentación de caracteres; Matrícula iraquí; reconocimiento de matrículas (LPR); diseño de placa; detección de placa de vehículo

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Section: Figure 2 Proposal System For License Plate Recognition Systemmentioning

confidence: 99%

Comparative Study between Iraqi and EU Vehicles License Plates in view of Segmentation and Recognition

2019

JAUS

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“…Images captured from a video camera are processed though a software which facilitates ANPR. The License Plate Recognition (LPR) system operates in four major steps, as given below [5,6]:…”

Section: A Backgroundmentioning

confidence: 99%

Feasibility of Efficient Number Plate Recognition using Morphological Dilation and Support Vector Machine

Vaishnav¹,

Ahuja²,

Mandot³

2019

IJRTE

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Intelligent data acquisition of vehicle number plate plays a significant role to recognize a vehicle and it automatic parking, traffic movement and scheduling, tracking of stolen vehicle, and many more. Although different methodologies of automatic number plate reading have developed alongwith their algorithms, still an efficient number plate recognition technique for better segmentation and recognition of the captured number plate using Morphological Dilation and Support Vector Machine (SVM) are expected to be helpful. In this paper, we present a modified method for recognition of contents of number plate using morphological dilation and SVM. We have compared our results with those from the existing models using Wavelet Transform and Artificial Neural Network techniques. Superiority of present methodology is established using parameters like image segmentation and recognition.

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“…[5]. In the paper [2], they attempt to provide an improve and complete sight of the research work made in the area of LP detection and recognition and the methods working in rising a License plate Recognition (LPR) system. In this analysis contrast the License Plate Recognition methods based on dissimilar criterion like character segmentation.…”

Section: Related Workmentioning

confidence: 99%

“…In this technique with the help of text-line construction and multilevel RBFNN a license plate is detected. According to Baoming Shan[2] the text line construction result and the vehicle license plate character arrangement characteristics the license plate location is decided. And to create more precise license plate localization a locally best adaptive binarization is exploiting.…”

mentioning

confidence: 99%

License Plate Recognition for Indian Number Plate: A Review

More¹,

Tidke²

2014

IJCA

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Traffic security and its management controls and supervised the number of vehicles. The traffic management system broadly used license plate recognition for them whose owner has dumped the traffic laws or to find the stolen vehicles. In most of the traffic related application like stolen vehicles, road traffic monitoring airport gate monitoring, speed monitoring, and automatic parking lots access control, for all this purpose the key technique are used which are vehicle license plate detection and recognition. It is basically the skill of automatically extract and recognition of the vehicle license number plate character from the captured image. The method of number plate recognition faces the problem of feature selection process. The present methods of number plate recognition system only focus on the local, global and neural network process of feature extraction and process of detection. The detection ratio of number plate recognition was improved by the optimized feature selection process. Here in this paper novel method for license plate recognition is proposed, which is based on wavelet transform function as well as comparing the proposed methodology with correlation based method for the detection of number plate.

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Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF Neural Network

Cited by 30 publications

References 13 publications

Comparative Study between Iraqi and EU Vehicles License Plates in view of Segmentation and Recognition

Comparative Study between Iraqi and EU Vehicles License Plates in view of Segmentation and Recognition

Feasibility of Efficient Number Plate Recognition using Morphological Dilation and Support Vector Machine

License Plate Recognition for Indian Number Plate: A Review

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