Abstract
<p>License Plate Detection and Localization (LPDL) is known to have become one of the most progressive and growing areas of study in the field of Intelligent Traffic Management System (ITMS). LPDL provides assistance by being able to specifically locate a vehicle’s number plate which is an essential part of ITMS, that is used for automatic road tax collection, traffic signals defilement implementation, borders and payments barriers and to monitor unlike activities. Organizations can deploy the number plate detection and recognition system to track their vehicles and to monitor each of them in their vital business activities like inbound and outbound logistics, find the exact location of their vehicles and organize entrance management. A competent algorithm is proposed in this paper for number plate detection and localization based on segmentation and morphological operators. Thus, the proposed algorithm it works on enhancing the quality of the image by applying morphological operators afterwards to segment out license plate from the captured image. No assumptions about the license plate color, style of font, size of text and type of material the plate is made of. The results reveal that the proposed algorithm works perfectly on all kinds of license plates with 93.43% efficiency rate. </p>
Highlights
Security, one of the most resounding words in today’s world, has influenced our lives in many different aspects
Joarder et al (2012) claimed that automatic number plate recognition is one of the important applications that can be used by the government, business’ and persons to cope with for example the traffic of vehicles, control the traffic violation, parking lots management, organization entrance management, automatic toll collection enforcement, traffic law enforcement, border surveillance and stolen vehicle search
This study proposes an intelligent License Plate Detection and Localization (LPDL) system for captured images without considering the license plate color, size, style of font, size of text and the types of plates used
Summary
One of the most resounding words in today’s world, has influenced our lives (as individuals, groups, and organizations) in many different aspects. Methods and techniques have been proposed to solve efficiently the LPDL system based on general feature of the number plates like shape, color, standard font and style, or by searching for a signature (Parker & Federl, 1996; Kim et al, 1999; Vichik et al, 1999; Ponce et al, 2000; Qadri & Asif, 2009). Earlier methods (Laplacian, Sobel, Prewitt, Canny, and Roberts operators) which used such common features from edge detection (Ponce et al, 2000; Chanson & Roberts, 2001; Hsieh et al, 2002; Kim et al, 2002) have a major drawback which is that edge-based techniques cannot be applied to advance and composite applications in isolation, as they are extremely sensitive to undesirable edges This would present a higher edge magnitude in addition or alternatively its variance. The proposed scheme is meant to be light weighted and inexpensive, it can be useful for real time implementation for recognizing number plates in different scenarios
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