Paper Info
Title
Blob extraction based character segmentation method for automatic license plate recognition system
Abstract
A character segmentation algorithm for automatic license plate recognition is presented in this paper. Character regions are selected through binarization, connected component analysis, and character recognition. A blob analysis operation excludes noisy blobs, merges fragmented blobs, and splits clumped blobs. A character segmentation module achieved an accuracy rate of 97.2%. The recognition accuracy of the complete system with license plate localization was 90.9%. In depth analysis of failure cases is also provided for better understanding of the algorithm and a future development direction.
Year
DOI
Venue
2011
10.1109/ICSMC.2011.6084002
SMC
Keywords
Field
DocType
recognition accuracy,clumped blobs,character segmentation,connected component analysis,character segmentation method,license plate localization,image segmentation,character recognition,automatic license plate recognition system,character regions,character segmentation module,fragmented blobs,binarization,anpr,license plate,character segmentation algorithm,blob analysis operation,blob extraction,principal component analysis,noisy blobs,accuracy,merging
Computer vision,Scale-space segmentation,Character recognition,Pattern recognition,Computer science,Segmentation,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Connected-component labeling,Principal component analysis,License
Conference
ISSN
ISBN
Citations 
1062-922X
978-1-4577-0652-3
3
PageRank 
References 
Authors
0.39
0
4
Name
Order
Citations
PageRank
Youngwoo Yoon1236.15
Kyu-Dae Ban241.75
Ho-sub Yoon3383.28
Jaehong Kim438341.59