Real-time automatic license plate recognition for CCTV forensic applications

Sarfraz, M. Saquib; Shahzad, Atif; Elahi, Muhammad Adnan; Fraz, Muhammad Moazam; Zafar, I.; Edirisinghe, Eran A.

doi:10.1007/s11554-011-0232-7

Cited by 59 publications

(19 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is to be noted that only few algorithms work for real-time video image of a number plate [33], [30], [39], [51], [61], otherwise static image of number plate is remitted to ANPR for further processing. In Table 1, different plate segmentation detection success rate against plate resolution of different ANPR is depicted.…”

Section: Discussionmentioning

confidence: 99%

“…To detect license plate from CCTV footage, M.S.Sarfraz et al [39] proposed a novel approach for efficient localization of license plates in video sequence and the use of a revised version of an existing technique for tracking and recognition. The authors proposed a novel solution for adjusting varying camera distance and diverse lighting conditions.…”

Section: (A)mentioning

confidence: 99%

See 1 more Smart Citation

Automatic Number Plate Recognition System (ANPR): A Survey

Patel¹,

Shah²,

Patel³

2013

IJCA

147

View full text Add to dashboard Cite

Traffic control and vehicle owner identification has become major problem in every country. Sometimes it becomes difficult to identify vehicle owner who violates traffic rules and drives too fast. Therefore, it is not possible to catch and punish those kinds of people because the traffic personal might not be able to retrieve vehicle number from the moving vehicle because of the speed of the vehicle. Therefore, there is a need to develop Automatic Number Plate Recognition (ANPR) system as a one of the solutions to this problem. There are numerous ANPR systems available today. These systems are based on different methodologies but still it is really challenging task as some of the factors like high speed of vehicle, non-uniform vehicle number plate, language of vehicle number and different lighting conditions can affect a lot in the overall recognition rate. Most of the systems work under these limitations. In this paper, different approaches of ANPR are discussed by considering image size, success rate and processing time as parameters. Towards the end of this paper, an extension to ANPR is suggested.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: (A)mentioning

confidence: 99%

Automatic Number Plate Recognition System (ANPR): A Survey

Patel¹,

Shah²,

Patel³

2013

IJCA

147

View full text Add to dashboard Cite

show abstract

“…In [14], the authors proposed a novel approach for efficient localization of license plates from the CCTV footage. In this method, revised version of an existing technique for tracking and recognition is proposed.…”

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

“…The remaining candidate regions are then checked based on their texture similarity to license plate-like areas. Then locations and the measurements of the four corners of the detected number plates are returned [8]. Each detected number plate is considered as the location of a vehicle which must be recognized.…”

Section: A Automatic Licence Number Plate (Alnp) Detectionmentioning

confidence: 99%

“…The De-Skewing algorithm which is proposed to tackle this problem is explained below. Coherent Point Drift (CPD) [9], is a probabilistic technique for non-rigid registration of point sets. The CPD technique concurrently finds the non-rigid transformation and the correspondence amongst two point sets using motion coherence, regardless of the transformation model.…”

Section: B De-skewingmentioning

confidence: 99%