Towards improving capacity of cover image based on LSB

Aug 21, 2014

10 likes | 86 Views

Towards improving capacity of cover image based on LSB.

Share Presentation

Embed Code

Link

chongjian liudepartment
auckland
human visual system
y k lee
size lsb
steganographic model

skah

Download Presentation

Towards improving capacity of cover image based on LSB

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Towards improving capacity of cover image based on LSB Abstract: Steganography aims to secretly transmit message by embedding them in other media, such as digital images. Its criterion is to hide messages in such a way so that they are not perceivable to Human Visual System (HVS). A number of ways exists to hide information in digital images or so-called cover images. The Least-Significant Bit (LSB) insertion is a common, simple approach to imbedding information in an image. However it is still an open issue that how to decide on maximal embedding capacity for each pixel. This report will review “a high capacity image steganographic model” proposed by Y.K.LEE and L.H.CHEN [1]. Based on variable-size LSB insertion, the proposed model tries to increase the embedding capacity of a grey-scale image and meanwhile to reduce the losses of its fidelity. Chongjian LiuDepartment of Computer ScienceUniversity of Auckland

INAOE at ImageCLEF2007 Towards Annotation based Image Retrieval

INAOE at ImageCLEF2007 Towards Annotation based Image Retrieval. H. Jair Escalante, Carlos Hernández, Aurelio López, Heidi Marín, Manuel Montes , Eduardo Morales, Enrique Sucar, Luis Villaseñor Language Technologies Laboratory National Institute of Astrophysics, Optics and Electronics

1.19k views • 17 slides

Steganography in WebP image using LSB embedding

Steganography in WebP image using LSB embedding. Master’s project d efense By Manchu Viswam. Introduction. Steganography is the art of hiding information in ways that prevent the detection of hidden messages. Steganography means “ covered writing .”

588 views • 34 slides

[Image Similarity Based on Histogram]

[Image Similarity Based on Histogram]. Wang wan 581 Project Prof. Longin Jan Latecki. Image Similarity. Pixel based Histogram based Shape similarity Etc. (3, 8, 5). What is histogram?. Image Histogram. If f :[1, n]x[1, m]  [0, 255] is a gray value image,

330 views • 17 slides

Improving image quality of synthetically zoomed tomographic image

Improving image quality of synthetically zoomed tomographic image. -Neha Dixit. Presentation layout . Tomography basics/background Problem statement and challenges faced Existing approaches Proposed approach Results Conclusion Future work. Tomographic image reconstruction.

779 views • 60 slides

Image processing based on sparse representation

Image processing based on sparse representation. http://lear.inrialpes.fr/people/mairal/resources/pdf/ERMITES10.pdf. Thanks Any Questions?.

793 views • 29 slides

Image Compression Based on Regression Equation

Image Compression Based on Regression Equation. Advisor: H. C. Wu, Y. K. Chan Speaker: Hsin-Nan Tsai ( 蔡信男 ) Date: May 4, 2005. Outline. Introduction The proposed method Experimental results Conclusions. Introduction. YIQ model Quadtree structure Edge detection

502 views • 41 slides

Book Cover Image Program

Book Cover Image Program. Li Yiu On (yoli@hkbu.edu.hk) Senior Assistant Librarian (Systems) Hong Kong Baptist University Library. 13 Feb., 2009 JULAC Libraries Forum University of Hong Kong. Outline. Background Disadvantages of a Single Vendor Model

732 views • 59 slides

High-capacity image hiding scheme based on vector quantization

High-capacity image hiding scheme based on vector quantization. Authors: Yu-Chen Hu Source: Pattern Recognition, vol. 39, pp. 1715-1724, 2006 Speaker: Shu-Fen Chiou( 邱淑芬 ) Date: 2006/10/19. Outline. Introduction Proposed method Experimental results Conclusion Comment.

352 views • 22 slides

Capacity Building Programme on International Trade towards enhancement of

Traceability and Traceability initiatives by APEDA. Capacity Building Programme on International Trade towards enhancement of Competitiveness of Indian Agriculture 5th-9 th September, 2011 IIFT,New Delhi, India _____________ Sudhanshu Deputy General Manager, APEDA,

792 views • 58 slides

Image steganographic scheme based on pixel-value differencing and LSB replacement methods

Image steganographic scheme based on pixel-value differencing and LSB replacement methods. H.-C. Wu, National Taichung Institute of Technology, N.-I. Wu, Chaoyang University of Technology, M.-S. Hwang and C.-S. Tsai, National Chung Hsing University, Taichung, Taiwan, R.O.C .

531 views • 11 slides

Method of Copy-Cover Image Forgery Detection

Method of Copy-Cover Image Forgery Detection. Sheng-Wen Peng 31004109. Outline. Introduction WATERMARKING FOR IMAGE AUTHENTICATION COPY-COVER IMAGE FORGERY DETECTION PCA Domain Method EXPERIMENTAL RESULTS. Introduction.

436 views • 22 slides

Image cryptosystems based on PottsNICA algorithms

Image cryptosystems based on PottsNICA algorithms. Meng-Hong Chen Jiann-Ming Wu Department of Applied Mathematics National Donghwa University. Blind Source Separation (BSS). Sources. Unknown Mixing Structure. Observations. BSS by PottsICA. PottsNICA. Observations

303 views • 21 slides

Background Subtraction based on Cooccurrence of Image Variations

Background Subtraction based on Cooccurrence of Image Variations. Seki, Wada, Fujiwara & Sumi - 2003 Presented by: Alon Pakash & Gilad Karni. Motivation. Detecting foreground objects in dynamic scenes involving swaying trees and fluttering flags. Dynamic Scenes.

955 views • 77 slides

Image Segmentation based on multicue fusion

Image Segmentation based on multicue fusion. XiaoweiGeng 2007.09.24. Content. Introduction about image segmentation image segmentation priciples Main Process Related Results. Main Principles. Conditional Random Fields Model Mean Shift For color likelihood estimation

364 views • 24 slides

Improving the image of social work

Improving the image of social work. Mark Ivory, Strategic Media Manager, The College of Social Work. Journalists told the Social Work Task Force about the... absence of media expertise within social work

393 views • 25 slides

Towards Virtualization of User Interfaces based on UsiXML

Web3D Symposium 2005 March 29 - April 1 2005, Bangor, UK. Towards Virtualization of User Interfaces based on UsiXML. J. P. Molina 1,2 , J. Vanderdonckt 1 , F. Montero 1,2 , P. González 1 1 Université catholique de Louvain 2 University of Castilla-La Mancha. www.usixml.org. Contents.

529 views • 43 slides

[Image Similarity Based on Histogram]

191 views • 17 slides

Image Filtering Based on GMSK

Image Denoising is an important pre processing task which is used before further processing of image. The purpose of denoising is to remove the noise while retaining the edges and other detailed features. This noise gets introduced during the process of acquisition, transmission and reception and storage and retrieval of the data. Due to this there is degradation in visual quality of image. The noises which are of major considerations are Additive White Gaussian Noise AWGN and Impulsive Noise. Sehba Yousuf | Er. Arushi Baradwaj "Image Filtering Based on GMSK" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: https://www.ijtsrd.com/papers/ijtsrd18403.pdf Paper URL: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18403/image-filtering-based-on-gmsk/sehba-yousuf

43 views • 3 slides

Image Retrieval Based on Regions of Interest

Image Retrieval Based on Regions of Interest. Source : KNOWLEDGE AND DATA ENGINEERING, IEEE Vol.: 15, No. 4, JULY,2003 pp.1045 - 1049 Author : Khanh Vu, Kien A. Hua, Senior Member, Wallapak Tavanapong Reporter : Shing-Shoung Wang Date : 2005/5/3.

164 views • 15 slides

LSB Based Image Steganography for Information Security System

Information hiding in a cover file is one of the most modernized and effective ways for transferring secret message from sender to receiver over the communication channel. There are many steganographic techniques for hiding secret message in image, text, audio, video and so on. Image Steganography is also one of the common methods used for hiding the information in the cover image. In this research work, the secret message is hidden in a cover image file using image steganography. LSB is very efficient algorithm used to embed the information in a cover file. The LSB based image steganography with various file sizes is analyzed and illustrated their results. Bitmap .bmp image is used as a cover image file to implement the proposed system. The detail Least Significant Bit LSB based image steganography is introduced. In this paper, the new embedding algorithm and extracting algorithm are presented. While embedding the secret message in a cover image file, the starting embedded pixel is chosen according to public shared key between sender and receiver. The original cover image and embedded image with secret message are analyzed with PSNR values and SNR values to achieve security. The resulting embedded image shows the acceptable PSNR and SNR values while comparing with the original cover image. The proposed system can help the information exchanging system over communication media. Aung Myint Aye "LSB Based Image Steganography for Information Security System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: https://www.ijtsrd.com/papers/ijtsrd18995.pdf Paper URL: http://www.ijtsrd.com/computer-science/computer-security/18995/lsb-based-image-steganography-for-information-security-system/aung-myint-aye

90 views • 7 slides

Review Paper on LSB Based Stegnography to Enhance Image Security

Steganography is the technique of hiding a secret message or information in a cover message like an image, text or sound in such a way that only the desired or intended recipient knows about the existence of the secret data. It can be defined as the study of invisible communication which usually deals with the technique of hiding the existence of the secret message. The hidden message may be in the form of text, image, audio and video etc. An image after inserting the secret message into it by using a stego key is known as a stego image. Nowadays steganography is important due to an exponential growth in secret communication by potential computer users over the internet. In this paper we have analyzed the various steganography techniques and observed that the security of the secret message can be enhanced by random selection of the pixels for substitution in LSB steganography. Further the error metrics PSNR Peak Signal to Noise Ratio should be high and MSE Mean Square Error should be low indicating good quality re construction. Naveen Verma | Preeti Sondhi | Gargi Kalia "Review Paper on LSB Based Stegnography to Enhance Image Security" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25326.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/25326/review-paper-on-lsb-based-stegnography-to-enhance-image-security/naveen-verma

75 views • 4 slides

More Related