Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/1585
Title: Morphology Based Approach to Recognize Number Plates in India
Authors: Pandya, Phalgun
Supervisor: Singh, M. D.
Keywords: LPR;ANPR;Morphology
Issue Date: 7-Oct-2011
Abstract: Along with the progress of the society, the rhythm of people's life becomes quick, which makes the need of automobile inevitable. Also, the fast development of computers, communication and computer network techniques, makes the transportation management automation an inevitable goal. As an important means of automatic traffic management especially red light signal violation, license plate recognition technique plays an increasingly obvious role. Automatic License Plate Recognition is an essential stage in intelligent traffic systems. The use of vehicles has been increasing because of population growth and human needs in recent years. Therefore, control of vehicles is becoming a big problem and much more difficult to solve. The License Plate Recognition (LPR) technology applies image processing and character recognition techniques to identify vehicles by automatically reading their license plates. The automatic license plate recognition, which is an important technique to obtain traffic information, mixes computer vision, image processing techniques and pattern recognition techniques. In a vehicle license plate recognition system, plate region detection is the key step before the final recognition. This thesis introduces the whole process of plate region detection. This thesis entitled “Morphology Based Approach to Recognize Number Plates in India” deals with a novel approach for locating the license plate. By using simple preprocessing techniques and morphology based techniques, this system locates the license plate and then recognizes the characters of the License plate. The experimental results show that this new algorithm is efficient and robust in detecting license pates of Indian vehicles.
Description: M.E. (Electronic Instrumentation and Control)
URI: http://hdl.handle.net/10266/1585
Appears in Collections:Masters Theses@EIED

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