Detection of Oriented Number Plate in Vehicle Using Autocorrection Feature From Gray Level Co-Occurence Matrix

Abstract

The efficiency of an automatic number plate recognition system depends directly on the proper effective preprocessing of the number plate. The OCRs available for recognition are capable of reading the number plates which are in proper orientation of 00. In many situations the vehicle number plates captured may be in any different orientation like 900, 1800 and 2700. These orientations in number plates are due to declamping of number plate at one end or toppling of vehicle. Such differently oriented number plates cannot be subjected for reading by OCRs and such situations require the system to detect the direction of orientation and correct the same before subjecting the same for reading. This paper proposes a work to detect the orientation of segmented number plates from vehicle image using autocorrelation feature from gray level cooccurrence matrix. A good volume of training samples are generated synthetically to train the system and the system is tested using sufficient test samples. The results of system shows an overall efficiency of 65.61% and performs an essential preprocessing in an automatic number plate recognition system.