Recognition of license plate images: issues and perspectives

Shridhar, M.; Miller, Joan G.; Houle, G.; Bijnagte, L.

doi:10.1109/icdar.1999.791714

Cited by 29 publications

(7 citation statements)

References 2 publications

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“…Consequently, traditional graphics recognition tasks may be updated to accommodate document images captured through a hand-held camera in an uncontrolled environment. Examples of such tasks include analysis of documents captured by a digital camera, OCR in images of books on bookshelves [12], analysis of images of outdoor signs [7], license plate recognition [13], and text identification and recognition in image sequences for video indexing [10]. Consequently, distortions characteristic of such situations should be addressed.…”

Section: Introductionmentioning

confidence: 99%

Document Image De-warping for Text/Graphics Recognition

Agam

2002

Lecture Notes in Computer Science

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Section: Introductionmentioning

confidence: 99%

Document Image De-warping for Text/Graphics Recognition

Agam

2002

Lecture Notes in Computer Science

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“…A complete HOV monitoring system suitable for the above applications will consist of an occupant detector and a license plate reader. Although substantial work has been reported in the technical literature regarding license plate readers [1]- [3], work for automated vehicle occupant detectors and counters is still in its infancy. There are three major technical challenges in the development of an automatic vehicle occupant detector/counter.…”

mentioning

confidence: 99%

A vehicle occupant counting system based on near-infrared phenomenology and fuzzy neural classification

Pavlidis

Morellas

Papanikolopoulos

2000

IEEE Trans. Intell. Transport. Syst.

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We undertook a study to determine if the automatic detection and counting of vehicle occupants is feasible. An automated vehicle occupant counting system would greatly facilitate the operation of freeway lanes reserved for buses, car-pools, and emergency vehicles (HOV lanes). In the present paper, we report our findings regarding the appropriate sensor phenomenology and arrangement for the task. We propose a novel system based on fusion of near-infrared imaging signals and we demonstrate its adequacy with theoretical and experimental arguments. We also propose a fuzzy neural network classifier to operate upon the fused near-infrared imagery and perform the occupant detection and counting function. We demonstrate experimentally that the combination of fused near-infrared phenomenology and fuzzy neural classification produces a robust solution to the problem of automatic vehicle occupant counting. We substantiate our argument by providing comparative experimental results for vehicle occupant counters based on visible, single near-infrared, and fused near-infrared bands. Interestingly, our proposed solution can find a more general applicability as the basis for a reliable face detector both indoors and outdoors.

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“…This system will solve so many problems for these city facilities which is hard to be controlled by human 24 hours. However, this system is still facing a lot of difficulties to be able to recognize license plates and one of these difficulties is the large variety of plate's layouts between the different countries and even across the same country cities [5]. This work tends to find an integrated System which can recognize these license plates automatically in real-time applications.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Method of Vehicle Number Plate Detection and Recognition

Lazrus¹,

Choubey²,

Gr³

2011

Int J Mach Intell

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Abstract-License plate location is an important phase in vehicle license plate recognition for intelligent transport systems. The objective of this work is to design and implement an efficient method for License Plate Recognition (LPR) of Indian License Plates. This paper presents a robust method of license plate location, segmentation and reorganization of the characters present in the located plate. The images of various vehicles have been acquired manually and converted in to gray-scale images. Then wiener2 filter is used to remove noise present in the plates. The segmentation of gray scale image generated by finding edges using Sobel filter for smoothing image is used to reduce the number of connected component and then bwlabel is used to calculate the connected component. Finally, single character is detected. The results show that the proposed method achieved accuracy of 98% by optimizing various parameters with higher recognition rate than the traditional methods

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Recognition of license plate images: issues and perspectives

Cited by 29 publications

References 2 publications

Document Image De-warping for Text/Graphics Recognition

Document Image De-warping for Text/Graphics Recognition

A vehicle occupant counting system based on near-infrared phenomenology and fuzzy neural classification

An Efficient Method of Vehicle Number Plate Detection and Recognition

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