Automatic Localization and Recognition of License Plate Characters for Indian Vehicles

Automatic License Plate Recognition (ALPR) is a challenging area of research due to its importance to variety of commercial applications. ALPR systems are widely implemented for automatic ticketing of vehicles at car parking area, tracking vehicles during traffic signal violations and related applications with huge saving of human energy and cost. The overall problem may be subdivided into three distinct key modules: (a) localization of license plate from vehicle image, (b) segmentation of the characters within the license plate and (c) recognition of segmented characters within the license plate. The main function of the module (a) is to find out the potential regions within the image that may contain the license plate. The function of module (b) is to isolate the foreground characters from the background within the detected license plate region. And the function of the module (c) is to recognize the segments in terms of known characters or digits. Though modules (b) and (c) employ most of the traditional methods available to the technologists, module (a) i.e. localization of potential license plate regions(s) from vehicle images is the most challenging task due to the huge variations in size, shape, color, texture and spatial orientations of license plate regions in such images. In general, objective of any ALPR system is to localize potential license plate region(s) from the vehicle images captured through a road-side camera and interpret the segmented characters present therein using an Optical Character Recognition (OCR) system, to get the license number of the vehicle. Again, an ALPR system can have two varieties: on-line ALPR system and off-line ALPR system. In an online ALPR system, the localization and interpretation of license plates take place instantaneously from the incoming video frames, enabling real-time tracking of moving vehicles through the surveillance camera. On the other hand, an offline ALPR system captures the vehicle images and stores them in a centralized data server for further processing, i.e. for interpretation of vehicle license plates. The objective of the current work falls under the second category of ALPR system. In this work, real time vehicle images are captured from a road-side surveillance camera automatically throughout day and night. The images are stored in a centralized data server. A never ending process takes the stored images sequentially and interprets the license number of the vehicle. An innovative idea using statistical distribution of the vertical edges is used for localization of license plate, connected component labeling is used for segmentation of the characters and template matching using an innovative matching technique is used for recognition of the characters. The performance of the system is measured at the three levels, i.e. localization level, segmentation level and recognition level and the result seems to be quite satisfactory