License plate recognition with multi-threshold based on entropy

Author

Abidin, Nadiah H. Z. ; Abdullah, S.N.H.S. ; Sahran, S. ; PirahanSiah, F.

Author_Institution

Center for Artificial Intell. Technol., Univ. Kebangsaan Malaysia, Bandar Baru Bangi, Malaysia

fYear

2011

fDate

17-19 July 2011

Firstpage

1

Lastpage

6

Abstract

Among all the existing segmentation techniques, thresholding technique is one of the most popular one due to its simplicity, robustness and accuracy. Multi-thresholding is an important operation in many analyses which is used in many applications. Selecting correct thresholds to get better result is a critical issue. In this research, a multilevel thresholding method is proposed based on combination of maximum entropy. The maximum entropy thresholding algorithm selects several threshold values by maximizing the cross entropy between the original image and the segmented image. This method can effectively integrate partial range of the image histogram. The proposed algorithm is compared with single thresholding method based on maximum entropy and multilevel thresholding method The proposed multi thresholding method is tested on license plate application. From the experiment, multi-threshold method further improved to increase the segmentation accuracy in the future.

Keywords

image segmentation; maximum entropy methods; optical character recognition; image histogram; image segmentation; license plate recognition; maximum entropy thresholding algorithm; multilevel thresholding method; multithreshold technique; original image; single thresholding method; Accuracy; Character recognition; Entropy; Feature extraction; Image segmentation; Licenses; PSNR; OCR; peak signal to noise ratio; segmentation; thresholding;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering and Informatics (ICEEI), 2011 International Conference on

Conference_Location

Bandung

ISSN

2155-6822

Print_ISBN

978-1-4577-0753-7

Type

conf

DOI

10.1109/ICEEI.2011.6021627

Filename

6021627