License plate recognition with multi-threshold based on entropy

Nor Hanisah Zainal Abidin, Siti Norul Huda Sheikh Abdullah, Shahnorbanun Sahran, Farshid Pirahansiah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011 - Bandung
Duration: 17 Jul 201119 Jul 2011

Other

Other2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
CityBandung
Period17/7/1119/7/11

Fingerprint

Entropy
Experiments

Keywords

  • OCR
  • peak signal to noise ratio
  • segmentation
  • thresholding

ASJC Scopus subject areas

  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Zainal Abidin, N. H., Sheikh Abdullah, S. N. H., Sahran, S., & Pirahansiah, F. (2011). License plate recognition with multi-threshold based on entropy. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011 [6021627] https://doi.org/10.1109/ICEEI.2011.6021627

License plate recognition with multi-threshold based on entropy. / Zainal Abidin, Nor Hanisah; Sheikh Abdullah, Siti Norul Huda; Sahran, Shahnorbanun; Pirahansiah, Farshid.

Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011. 6021627.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zainal Abidin, NH, Sheikh Abdullah, SNH, Sahran, S & Pirahansiah, F 2011, License plate recognition with multi-threshold based on entropy. in Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011., 6021627, 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011, Bandung, 17/7/11. https://doi.org/10.1109/ICEEI.2011.6021627
Zainal Abidin NH, Sheikh Abdullah SNH, Sahran S, Pirahansiah F. License plate recognition with multi-threshold based on entropy. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011. 6021627 https://doi.org/10.1109/ICEEI.2011.6021627
Zainal Abidin, Nor Hanisah ; Sheikh Abdullah, Siti Norul Huda ; Sahran, Shahnorbanun ; Pirahansiah, Farshid. / License plate recognition with multi-threshold based on entropy. Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011.
@inproceedings{7f64520af8984eb6b2048044ffabf47d,
title = "License plate recognition with multi-threshold based on entropy",
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 = "OCR, peak signal to noise ratio, segmentation, thresholding",
author = "{Zainal Abidin}, {Nor Hanisah} and {Sheikh Abdullah}, {Siti Norul Huda} and Shahnorbanun Sahran and Farshid Pirahansiah",
year = "2011",
doi = "10.1109/ICEEI.2011.6021627",
language = "English",
isbn = "9781457707520",
booktitle = "Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011",

}

TY - GEN

T1 - License plate recognition with multi-threshold based on entropy

AU - Zainal Abidin, Nor Hanisah

AU - Sheikh Abdullah, Siti Norul Huda

AU - Sahran, Shahnorbanun

AU - Pirahansiah, Farshid

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - OCR

KW - peak signal to noise ratio

KW - segmentation

KW - thresholding

UR - http://www.scopus.com/inward/record.url?scp=80054049899&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80054049899&partnerID=8YFLogxK

U2 - 10.1109/ICEEI.2011.6021627

DO - 10.1109/ICEEI.2011.6021627

M3 - Conference contribution

SN - 9781457707520

BT - Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011

ER -