iosr-JCE   Volume-1 ~ Issue-6

Abstract: Over the past decade more and more users of the Internet rely on the search engines to help them find the information they need. However the information they find depends to a large extent, on the ranking mechanism of the search engines they use. Not surprisingly it in general consists of a large amount of information that is completely irrelevant. Text summarization is a process of reducing the size of a text while preserving its information content. Text Summarization is an emerging technique for understanding the main purpose of any kind of documents. To visualize a large text document within a short duration and small area like PDA screen, summarization provides a greater flexibility and convenience. This research focuses on developing a statistical automatic text summarization approach, K-mixture probabilistic model, to enhancing the quality of summaries. Sentences are ranked and extracted based on their semantic relationships significance values. The objective of this research is thus to propose a statistical approach to text summarization.
Keywords - Extraction, Keywords, Statistical approach, Text Summarization, Webpage.

[1] JIANG Xiao-YU," Improving the Performance of Text Categorization using Automatic Summarization", International Conference on Computer Modeling and Simulation 978-0-7695-3562-3/09 ©2009 IEEE.
[2] Khushboo S. Thakkar," Graph –Based Algorithms for Text Summarization", Third International Conference on Emerging Trends in Engineering and Technology 978-0-7695-4246-1/10©2010IEEE.
[3] Munesh Chandra," A Statistical approach for Automatic Text Summarization by Extraction"
2011 International Conference on Communication Systems and Network Technologies 978-0-7695-4437-3/11©2011 IEEE.
[4] LiChengcheng,"Automatic Text Summarization Based on Rhetorical Structure Theory", 2010 International Conference on Computer Application and System Modeling 978-1-4244-7237-6©2010 IEEE.
[5] Jagdish S KALLIMANI," Information Retrieval by Text Summarization for an Indian Regional Language",978-1-4244-6899-7/10@2010IEEE.
[6] Tengfei Ma,"Multi Document Summarization Using Minimum Distortion", 2010 IEEE International Conference on Data Mining 1550-4786/10©2010 IEEE.
[7] ZHANG Pei-ying," Automatic Text Summarization based on sentences clustering and extraction", 978-1-4244-4520-2/09©2009 IEEE.
[8] Celal Cigir,"Generic Text Summarization for Turkish", 978-1-4244-5023-7/09©2009 IEEE.
[9] Md.MohsinAli,"Multi-document Text Summarization: SimWithFirst Based Features and Sentence Co-selection Based Evaluation", 2009 International Conference on Future Computer and Communication 978-0-7695-3591-3/09©2009 IEEE.

Abstract: fingerprint authentication is implemented using many algorithms, which are based either on minutiae
analysis or non minutiae analysis. Preprocessing of the fingerprints is important for better accuracy.
Preprocessing includes segmentation and noise removal, which are considered two major steps in
preprocessing. In this paper segmentation is performed by using fuzzy logic system, as the edges of the finger
print plays a major role in the authentication fuzzy logic analysis improves sharpness of edges. This
preprocessed image is taken as the input, and then fingerprint authentication is performed on two modules
analysis on matching percentage is determined.
Keywords: authentication minutiae, segmentation preprocessing, matching percentage

[1] J. Yin, X. Yang, G. Zhang, C. Hun, "Two steps for fingerprint Segmentation," Image and Vision Computing, Vol. 25, pp. 1391–1403,2007.
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[6] Ursula Gonzales-Barron, Francis Butler. "A comparison of seven threshold techniques with the k-means clustering algorithm for measurement of bread-crumb features by digital image analysis," Journal of Food Engineering, Vol. 74, pp. 268–278, 2006.
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Abstract: In this paper, we are introducing a blind authentication method which is based on the secret sharing technique with a data repair capability for document images with the use of the PNG image. We generate an authentication signal for each block of a document image which, together with the block content in binary form, is transformed into several shares using the Shamir secret sharing scheme. These parameters are carefully chosen so that a large number of shares possible are generated and embedded into an alpha channel plane. Now the alpha channel plane is combined with the original image to form a PNG image. In the process of image authentication, an image block is marked as tampered if the authentication signal computed from the current block content does not match the one extracted from the shares embedded in the alpha channel plane. Repairing of data is now done to each tampered block by a reverse Shamir technique after collecting any two or more shares from unmarked blocks. Also a measure to protect the security of the data hidden in the alpha channel is proposed.
Index Terms: Image authentication, secret sharing, data repair, data hiding, and PNG (Portable Network Graphics) image.

[1] A Secret-Sharing-Based Method For Authentication Of Grayscale Document Images Via The Use Of The PNG Image With A Data Repair Capability By Che-Wei Lee, And Wen-Hsiang Tsai,At IEEE Transactions On Image Processing, Vol. 21, No. 1, January 2012.
[2] A Geometry-Based Secret Image Sharing Approach By Chien-Chang Chen And Wen- Yin Fu Department Of Computer Science Hsuan Chuang University Hsinchu, 300 Taiwan Journal Of Information Science And Engineering 24, 1567-1577(2008).
[3] Secret Sharing And Information Hiding By Shadow Images Chin-Chen Chang,The Duc Kieu Department Of Information Engineering And Computer Science, Feng Chia University, Taichung 40724, Taiwan, R.O.C.
[4] Secret Image Sharing With Steganography And Authentication Chang-Chou Lin, Wen-Hsiang Tsai,Department Of Computer And Information Science, National Chiao Tung University, Hsinchu 300,Taiwan,ROC Received 24 October 2002;Received In Revised Form 30 May 2003;Accepted 20 July 2003.
[5] Improvements Of Image Sharing With Steganography And Authentication Ching-Nung Yang , Tse- Shih Chen, Kun Hsuan Yu, Chung-Chun Wang Department Of Computer Science And Information Engineering, National Dong Hwa University, Sec. 2, Da Hsueh Rd., Hualien, Taiwan Received 22 October 2005; Received In Revised Form 18 November 2006; Accepted 26 November 2006.
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A New Approach," Comput. Vis. Graph. Image Process. Vol. 29, No. 3, Pp. 377–393, Mar.1985.
[7] A. Shamir, "How To Share A Secret," Commun.ACM,Vol.22, No.11,Pp.612–613,Nov. 1979.
[8] M. Wu And B. Liu, "Data Hiding In Binary Images For Authentication And Annotation," IEEE Trans.On Multimedia Vol.6,No. 4, Pp.528–538, 2004.
[9] H. Yang And A. C. Kot, "Binary Image Authentication With Tampering Localization By Embedding Cryptographic Signature And Block Identifier," IEEE Signal Processing Letters, Vol.13, No. 12,Pp. 741–744, Dec. 2006.
[10] H. Yang And A. C. Kot, "Pattern-Based Data Hiding For Binary Images Authentication By Connectivity-Preserving," IEEE Trans. On Multimedia, Vol. 9, No. 3, Pp. 475–486, April 2007.
[11] C. H. Tzeng And W. H. Tsai. "A New Approach To Authentication Of Binary Images For Multimedia Communication With Distortion Reduction And Security Enhancement," IEEE Communications Letters, Vol. 7, No. 9, Pp. 443–445.