Abstract-License plate location is an important phase in vehicle license plate recognition for intelligent transport systems. The objective of this work is to design and implement an efficient method for License Plate Recognition (LPR) of Indian License Plates. This paper 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 manually and converted in to gray-scale images. Then wiener2 filter is used to remove noise present in the plates. The segmentation of gray scale image generated by finding edges using Sobel filter for smoothing image is used to reduce the number of connected component and then bwlabel is used to calculate the connected component. Finally, single character is detected. The results show that the proposed method achieved accuracy of 98% by optimizing various parameters with higher recognition rate than the traditional methods

No abstract

No abstract

No abstract

Abstract-This paper presents a new methodology for the image segmentation and character recognition from standard Indian License number plates. Firstly it gets input of the segmented characters that is partitioned by our pixel Clustering partitioning method, in which we eliminate similar part from the character and match it by judging template and return identified character. This partitioning may be applied horizontally or vertically. Decision that the characters are partitioned horizontally or vertically depends on their subgroup. Before sub grouping we have to group the characters on the basis of the number of holes in it and then we subgroup on the basis of some similar features like | , / , \ , _ , ( , -, etc. If we have alphabet T and I where similar portion is I then both will go to same subgroup and we partition it horizontally. This method eliminates the problem of confusion between similar looking elements like C, G and T, I, 1, J etc by exploiting the small but important differences among them.