An algorithm for accuracy enhancement of license plate recognition

Zheng, Lihong; He, Xiangjian; Samali, Bijan; Yang, Laurence T.

doi:10.1016/j.jcss.2012.05.006

Cited by 57 publications

(39 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Edge-based methods [5][6][7][8][9][10][11][12][13][14][15][16][17][18] focus on the high contrast between text and background. The edges of text are identified, merged and then various techniques are applied to filter out the non-text regions.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

A New Approach to Extract Text from Images based on DWT and K-means Clustering

Ghai¹,

Gera²,

Jain³

2016

IJCIS

View full text Add to dashboard Cite

Text present in image provides important information for automatic annotation, indexing and retrieval. Therefore, its extraction is a well known research area in computer vision. However, variations of text due to differences in orientation, alignment, font, size, low image contrast and complex background make the problem of text extraction extremely challenging. In this paper, we propose a texture-based text extraction method using DWT with K-means clustering. First, the edges are detected from image by using DWT. Then, a small size overlapped sliding window is used to scan high frequency component sub-bands from which texture features of text and non-text regions are extracted. Based on these features, K-means clustering is employed to classify the image into text, simple background and complex background clusters. Finally, voting decision process and area based filtering are used to locate text regions exactly. Experimentation is carried out using public dataset ICDAR 2013 and our own dataset for English, Hindi and Punjabi text images for different number of clusters. The results show that the proposed method gives promising results with different languages in terms of detection rate (DR), precision rate (PR) and recall rate (RR).

show abstract

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

A New Approach to Extract Text from Images based on DWT and K-means Clustering

Ghai¹,

Gera²,

Jain³

2016

IJCIS

View full text Add to dashboard Cite

show abstract

“…As per [16], NP detection is a crucial step in an LPR system. The authors used global edge features and local Haar-like features for real-time traffic video.…”

Section: Review Of Existing Techniquesmentioning

confidence: 99%

A Novel Approach for Detecting Number Plate Based on Overlapping Window and Region Clustering for Indian Conditions

Patel¹,

Patel²,

Shah³

2015

IJIGSP

View full text Add to dashboard Cite

Abstract-Automatic Number Plate Recognition (ANPR) is becoming very popular and topic of research for the Intelligent Transportation System (ITS). Many researchers are working in this direction, as it is the topic of interest. In proposed system, we have presented a novel approach for number plate (NP) detection, which can be useful for Indian conditions. The system works well in different illumination conditions and 24 hours manner. Experiments achieved excellent accuracy of 98.88% of overall accuracy of NP detection on 90 vehicle images with different conditions and captured at different timing during day and night. Out of these 90 images, 89 images were segmented successfully. The minimum image size was 800 X 600 pixels. The system was developed using the Microsoft .NET 3.5 framework and Visual Studio 2008 as IDE with the Intel core i3 2.13 GHz processor having 3 GB RAM. Other systems discussed in this paper reported better processing time of less than 1s, but some of these systems work under restricted conditions and accuracy is also not as good as our system.

show abstract

“…Recognition of license plates using traffic video databases was carried out on global edge features with various parameters based on blob detection algorithm. The LPR results due to a faster and more precise identification (Lihong et al, 2013;Jianbin et al, 2009). Well-organized system has the ability to translate Arabic text found in images into English.…”

Section: Introductionmentioning

confidence: 99%

Automatic Recognition System of Vehicle Plate for Recording Incoming Vehicles to the University Campus and the Outgoing

El-Harby¹,

Behery²,

Al-Dhawi³

2017

American Journal of Applied Sciences

View full text Add to dashboard Cite

Automatic recognition of vehicle plate characters became a very important in our daily life because of the unlimited increase of vehicles that enter or leave a supervised area. This paper describes an automatic intelligent system that captures the images of vehicles and has the ability to recognize the plates of vehicles entering the university campus or leaving. A camera is built on the university gate for taking images of incoming or outgoing vehicles. A rear image of a vehicle is captured and processed. The system applies an intelligent filtering of the input image based on a set of filters removing unnecessary image elements preserving the position and shape of characters of the vehicle plate, histogram manipulation and edge detection techniques for plate localization and characters segmentation. Adaptive Neuro Fuzzy Inference System (ANFIS) is chosen as a classifier for recognizing the characters in the vehicle plates. This system can extracts the letters and numbers from vehicles plates. So, the extracted vehicle characters can be used to record the incoming vehicles to the university campus and the outgoing. The recognized vehicle characters are saved in the university database.

show abstract

An algorithm for accuracy enhancement of license plate recognition

Cited by 57 publications

References 15 publications

A New Approach to Extract Text from Images based on DWT and K-means Clustering

A New Approach to Extract Text from Images based on DWT and K-means Clustering

A Novel Approach for Detecting Number Plate Based on Overlapping Window and Region Clustering for Indian Conditions

Automatic Recognition System of Vehicle Plate for Recording Incoming Vehicles to the University Campus and the Outgoing

Contact Info

Product

Resources

About