A Lossless Recovery of Data Embedded in Color Image Based On Block Division Method
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 3
Abstract
Today, digital media are getting more and more popular. Not only multilevel images, video and audio are in digital form, but gray scale images are also digitized in many applications. Data transmitted over the internet can be hacked, so the data encryption becomes important. One of the encryption techniques is reversible data hiding. The major characteristic of this method is that it allows reconstruction of the original image from the stego image after extraction of data. Ni (NSAS) proposed the reversible data hiding based on histogram shifting. However the method had no provision of sending the peak point information required to extract the secret data. Later, Hwang (HKC) proposed a scheme based on histogram shifting to overcome this shortcoming. But this method decreases the data hiding capacity. In order to enhance data hiding capacity block division method is used. In this paper an algorithm for embedding data into color image is proposed. According to the proposed method , the reversible data hiding scheme for color images not only improves the original data hiding capacity but also attains the goal of lossless data recovery.
Authors and Affiliations
Samriti Sharma , Rekha Udabale , Snehal Shendkar , Prof. Sukhada Bhingarkar
Case Study of Survival Function under Strength Attenuation of System for Exponential Distribution
In this paper an expression for the reliability of a single component system is derived when the strength of the component and the imminent stresses on the system are random and follow non-identical Probability distribut...
A QOS AWARE QUANTITATIVE WEB SERVICE SELECTION MODEL
Web service is a core technology for sharing information resources and integrating processes in companies or organizations. As the number of applications connected by Web service is increased, the importance of Web servi...
A Novel flow for Reasoning of Medical Diagnostic System using Artificial Feed Forward Neural Networks
In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background. Various research...
SSM-DBSCANand SSM-OPTICS : Incorporating a new similarity measure for Density based Clustering of Web usage data.
Clustering web sessions is to group web sessions based on similarity and consists of minimizing the intra-group similarity and maximizing the inter-group similarity. Here in this paper we developed a new similarity measu...
EFFICIENT ALGORITHM FOR MINING FREQUENT ITEMSETS USING CLUSTERING TECHNIQUES
Now a days, Association rule plays an important role. The purchasing of one product when another product is purchased represents an association rule. The Apriori algorithm is the basic algorithm for mining association ru...