Volume 3 Number 4 (Aug. 2011)
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IJCEE 2011 Vol.3(4): 503-506 ISSN: 1793-8163
DOI: 10.7763/IJCEE.2011.V3.369

Entropy Based Data Hiding in Binary Document Images

Aihab Khan, Memoona Khanam, Saba Bashir, Malik Sikander Hayat Khiyal, Asima Iqbal, and Farhan Hassan Khan

Abstract—This research paper has presented a data hiding technique for binary document images. Entropy measure method is used to minimize the perceptual distortion due to embedding. The watermark extraction is a blind system because neither the original image nor the watermark is required for extraction. The document image is similar to any other image. The proposed method discovers the specific regions where minimum distortion delay exists due to embedding. For embedding, the blocks that exist in the area of small font sizes are selected. Experimental results show that marked documents have excellent visual quality and less computational complexity.

Index Terms—Binary Documents, Controlled Dilation, Data Hiding, Document images, Entropy, Watermarking.

Aihab Khan is with the Department of Software Engineering, Fatima Jinnah Women University, Rawalpindi, Pakistan. (aihabkhan@yahoo.com).
Memoona Khanam is with the Department of Electrical Engineering, Federal Urdu University of Arts, Science & Technology. Islamabad, Pakistan, (dr.mahayat@gmail.com).
Saba Bashir is with the Department of Computer Engineering, National University of Science and Technology. Islamabad, Pakistan.12,(saba.bashir3000@gmail.com).
Malik Sikander Hayat Khiyal, (m.sikandarhayat@yahoo.com).
Asima Iqbal, (asima781@yahoo.com).
Farhan Hassan Khan, (mrfarhankhan@yahoo.com)*.

Cite: Aihab Khan, Memoona Khanam, Saba Bashir, Malik Sikander Hayat Khiyal, Asima Iqbal,and Farhan Hassan Khan, "Entropy Based Data Hiding in Binary Document Images,"  International  Journal  of  Computer
and Electrical Engineering
vol. 3, no. 4, pp. 503-506, 2011.

General Information

ISSN: 1793-8163 (Print)
Abbreviated Title: Int. J. Comput. Electr. Eng.
Frequency: Quarterly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: INSPEC, Ulrich's Periodicals Directory, Google Scholar, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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