A novel design for vehicle license plate detection and recognition

License plate recognition (LPR) plays a major role in this busy world, as the number of vehicles increases day by day, theft of vehicles, breaking traffic rules, entering restricted area are also increases linearly, so to block this act license plate recognition system is designed. License Plate Recognition systems basically consist of 3 main processing steps such as: Detection of number plate, Segmentation of plate characters and Recognition of each character. Among this, character segmentation is a most challenging task, as the accuracy of the character recognition relies on the accuracy of the character segmentation. Problems of different lighting condition, adhesion, fracture, rivet, rotation degrades the accuracy of the character segmentation. So in order to overcome these problems and uplift the accuracy of character segmentation various algorithms are developed for this work. This thesis presents a robust method of license plate location, segmentation and reorganization of the characters present in the located plate. The images of various vehicles have been acquired and converted in to gray-scale images. Then noise present in the plates are removed and the segmentation of gray scale image generated by finding edges for smoothing image is used to reduce the number of connected component and then bw label is used to calculate the connected component. Finally, single character in the license plate is detected. The aim is to show that the proposed method achieved high accuracy by optimizing various parameters with higher recognition rate than the traditional methods.