AN APPROACH TO IMAGE COMPRESSION AND ENCRYPTION

Image compression scheme proposed by researchers have no consideration of security. Similarly image encryption scheme proposed by the authors have no consideration of image size. In this paper a simultaneous image compression and encryption scheme is discussed. The order of the two processes viz. compression and encryption is EC i.e. image encryption is performed first then the image compression is applied. For image encryption a symmetric key cryptography multiplicative cipher is used. Similarly for compression Discrete Cosine Transform is used. Image Compression is concerned with minimizing the number of bit required to represent an image. The compression can be lossless or lossy. Image Encryption is hiding image from unauthorized access with the help of secret key that key can be private or public

AN OVERVIEW OF IMAGE SEGMENTATION ALGORITHMS

Image segmentation is a puzzled problem even after four decades of research. Research on image segmentation is currently conducted in three levels. Development of image segmentation methods, evaluation of segmentation algorithms and performance and study of these evaluation methods. Hundreds of techniques have been proposed for segmentation of natural images, noisy images, medical images etc. Currently most of the researchers are evaluating the segmentation algorithms using ground truth evaluation of (Berkeley segmentation database) BSD images. In this paper an overview of various segmentation algorithms is discussed. The discussion is mainly based on the soft computing approaches used for segmentation of images without noise and noisy images and the parameters used for evaluating these algorithms. Some of these techniques used are Markov Random Field (MRF) model, Neural Network, Clustering, Particle Swarm optimization, Fuzzy Logic approach and different combinations of these soft techniques

Image Segmentation using Various Approaches

This paper addresses the issue of image segmentation. Image segmentation process is the main basic process or technique used in various image processing problem domains, for example, content based image retrieval; pattern recognition; object recognition; face recognition; medical image processing; fault detection in product industries; etc. Scope of improvement exists in the following areas: Image partitioning; color based feature; texture based feature, searching mechanism for similarity; cluster formation logic; pixel connectivity criterion; intelligent decision making for clustering; processing time; etc. This paper presents the image segmentation mechanism which addresses few of the identified areas where the scope of contribution exists. Presented work basically deals with the development of the mechanism which is divided into three parts first part focuses on the color based image segmentation using k-means clustering methodology. Second part deals with region properties based segmentation. Later, deals with the boundary based segmentation. In all these three approaches, finally the Steiner tree is created to identify the class of the region. For this purpose the Euclidean distance is used. Experimental result justifies the application of the developed mechanism for the image segmentation

A COMPARATIVE STUDY OF IMAGE FILTERING ON VARIOUS NOISY PIXELS

This paper deals with the comparative study of research work done in the field of Image Filtering. Different noises can affect the image in different ways. Although various solutions are available for denoising them, a detail study of the research is required in order to design a filter which will fulfill the desire aspects along with handling most of the image filtering issues. An output image should be judged on the basis of Image Quality Metrics for ex-: Peak-Signal-to-Noise ratio (PSNR), Mean Squared Error (MSE) and Mean Absolute Error (MAE) and Execution Time

PERFORMING MULTIPLICATIONS IN IMAGE FILTERING PROCESS USING VEDIC MATHEMATICS

Image filtering is a very important step in image processing. Filtering involves lots of multiplications which consumes time. Time required increases with the increase in the number of pixels. This paper proposes an approach for image filtering using Vedic Mathematic which performs faster multiplication compared to the conventional algorithms namely Booth 2, Booth 3 and Array Multiplication Algorithm thus reducing the time required for filtering of images. Experimentation is done using C language. Time required by the algorithms for filtering are then compared using the experimental results

Load Balancing Based Approach to Improve Lifetime of Wireless Sensor Network

ABSTRACT In wireless sensor network, clustering is used as an effective technique to achieve scalability, selforganization, power saving, channel access, routing etc.[3

Modeling of Biodiesel Plant Design: Data Estimation and Generation Based on Suppositions and Interpolation

This paper presents the approach for the Biodiesel plant design data estimation and generation to support the mathematical formulation of the model. Presented approach is based on certain suppositions. Design data is estimated by using actual fundamentals involved in the design of the resources and equipments. Later, the sample space is increased by generating the design data. Design data is generated using the concept of linear interpolation, where the basic data fitting model is developed and then the intermediate design data values are obtained to increase the sample space. This facilitates the formulation of mathematical model. Experimental results are obtained through the MATLAB implementation

An Approach to Image Compression with Partial Encryption without sharing the Secret Key

Existing methods when employ compression there is no consideration of security, similarly when it describe encryption there is no consideration of size i.e. compression. In this paper a simultaneous image compression and encryption scheme is discussed. The order of the two processes viz. compression and encryption is EC i.e. image encryption is performed first then the image compression is applied. For image encryption a symmetric key cryptography multiplicative cipher is used. Similarly for compression Discrete Cosine Transform is used. In the proposed approach a private key cryptography is used for encryption without sharing the secret key. But image transmission is required two times. Therefore to save the bandwidth partial encryption is carried out. Image compression is concerned with minimizing the number of bit required to represent an image. Image Encryption is hiding image from unauthorized access with the help of secret key that key can be private or public. Key word