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Localization of License Plate Number Using Dynamic Image

In this research, the design of a new genetic algorithm (GA) is introduced to detect the locations of license plate (LP) symbols. An adaptive threshold method is applied to overcome the dynamic changes of illumination conditions when Converting the image into binary. Connected component analysis technique (CCAT) is used to detect candidate objects inside the unknown image. A scale-invariant geometric relationship matrix is introduced to model the layout of symbols in any LP that simplifies system adaptability when applied in different http://kaashivinfotech.com/ http://inplanttrainingchennai.com/ http://inplanttraining-in-chennai.com/ http://internshipinchennai.in/ http://inplant-training.org/ http://kernelmind.com/ http://inplanttraining-in-chennai.com/ http://inplanttrainingchennai.com/ Contact Us 91 98406 78906, 91 90037 18877 kaashiv.info@gmail.com www.kaashivinfotech.com Shivanantha Building (Second building to Ayyappan Temple), X41, 5th Floor, 2nd avenue, Anna Nagar,Chennai-40

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Localization of License Plate Number Using Dynamic Image

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  1. AutomaticObjectIdentifier and ImageRecognizer (AOR) IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 18, NO. 2, APRIL 2014 Localization of License Plate Number Using Dynamic Image Processing Techniques and Genetic Algorithms

  2. A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional VenkatesanPrabu .J MANAGING DIRECTOR Microsoft Web Developer Advisory Council team member and a well known Microsoft Most Valuable Professional (MVP) for the year 2008, 2009, 2010,2011,2012,2013 ,2014. LakshmiNarayanan.J GENERAL MANAGER BlackBerry Server Admin. Oracle 10g SQL Expert. Arunachalam.J Electronic Architect Human Resourse Manager

  3. Abstract • In this research, the design of a new genetic algorithm (GA) is introduced to detect the locations of license plate (LP) symbols. An adaptive threshold method is applied to overcome the dynamic changes of illumination conditions when • Converting the image into binary. Connected component analysis technique (CCAT) is used to detect candidate objects inside the unknown image. A scale-invariant geometric relationship matrix is introduced to model the layout of symbols in any LP that simplifies system adaptability when applied in different • Countries. Moreover, two new crossover operators, based on sorting, are introduced, which greatly improve the convergence speed of the system. Most of the CCAT problems, such as touching or broken bodies, are minimized by modifying the GA to perform partial match until reaching an acceptable fitness

  4. Proposed System • In the projected system, the image are cleansed up before process and when cleanup up or enhancing the image it'll be fed into the system for Pattern recognition. • Individual things are separated humor divided and later the weather is scanned through our pattern recognition system. • After finding the individual object, our skilled system can establish the actual object owner (In our case, vehicle owner).

  5. Existing System • In the existing system, pictures the photographs were mechanically recognized supported the individual components within the images. • Automatic comparison of the known objects with the present trained objects can modify the user to recognize the objects • Amending the individual objects into a wholesome of objects enable the system to identify the particular owner from the database.

  6. System Requirements • Hardware Requirements: System : Pentium IV 2.4 GHz. Hard Disk : 80 GB. Floppy Drive : 1.44 Mb. Monitor : 15 VGA Colour. Mouse : Logitech. Ram : 1 GB or Above • Software Requirements: Operating system : Windows 7 Front End : Dotnet 4.0 (VS 2010) Backend : SQL Server 2008 R2

  7. Architecture Diagram

  8. Records Breaks Asia Book Of Records Tamil Nadu Of Records India Of Records MVP Awards World Record

  9. Services: A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional Inplant Training. Internship. Workshop’s. Final Year Project’s. Industrial Visit. Contact Us: +91 98406 78906,+91 90037 18877 kaashiv.info@gmail.com www.kaashivinfotech.com Shivanantha Building (Second building to Ayyappan Temple),X41, 5th Floor, 2nd avenue,Anna Nagar,Chennai-40.

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