ALPR System Under Varying Illumination and Motion Conditions

As the significance of open transportation framework expands a programmed license plate recognition (ALPR) has ended up being a critical examination issue. It is getting to be hard to monitor every vehicle for motivation behind law implementation and movement administration. ALPR prepared in numerous wise observation frameworks like, traffic management, security administration, programmed toll gathering framework and so forth. A number of methods have been proposed for license plate detection, each having its own advantages and disadvantages. The basic step in ALPR is accurate localization of number plate, segmentation, recognition. Algorithm for Automatic License Plate Recognition system have been developed for college premises successfully for image and video data. GMM based algorithm was carried out for extraction of license plates from video data by integrating the different controlling parameters. License plates are detected from a video frame effectively by using Harris corner detector. Segmentation results achieved was good by utilizing integrated approach of controlling parameters. Artificial neural network (ANN) had used for the recognition purpose and accuracy achieved was high, also data logging had been implemented successfully for future purpose.