Publication Type : Conference Paper
Publisher : International Conference on Innovations in Computer Science & Engineering (ICICSE-2015), Springer Singapore
Source : International Conference on Innovations in Computer Science & Engineering (ICICSE-2015), Springer Singapore, Singapore (2015)
Url : https://link.springer.com/chapter/10.1007/978-981-10-0419-3_5
ISBN : 9789811004193
Keywords : adaptive threshold, Artificial intelligence, Connected element tagging, Convergence, Crossover, Genetic algorithm, Image processing, matrix, Mutation
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2015
Abstract : Registration plate recognition plays a vital role in numerous applications in today's world. We also introduce a new approach using genetic algorithm to figure out the registration plate location. Fluctuating illumination conditions are taken care-of by adaptive threshold method. Connected element tagging is used to identify the objects in blindfolded regions. A matrix of invariant scale geometry is used for better system adaptability when applied to different plates. The convergence of genetic algorithm is greatly improved by the introduction of a newly created mutation and crossover operators. We also modify genetic algorithm to overcome the drawbacks of connected element method by importing partial matching of the characters. Finally, we take a look at the real-time challenges and remedies to it.
Cite this Research Publication : G. Joseph and Dr. Tripty Singh, “Registration Plate Recognition Using Dynamic Image Processing and Genetic Algorithm”, in International Conference on Innovations in Computer Science & Engineering (ICICSE-2015), Singapore, 2015.