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 value. The system is implemented using MATLAB and various image samples are experimented with to verify the distinction of the proposed system.
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