In this study, a new image inpainting approach using multiscale salient structure propagation is proposed. The proposed approach consists of four stages, namely, (1) detection of salient structure(s), (2) inpainting of salient structure(s), (3) inpainting of surrounding areas of salient structure(s) by modified ant colony optimization (ACO), and (4) inpainting of remaining missing regions. Based on the experimental results obtained in this study, as compared with four comparison approaches, the proposed approach provides the better image inpainting results. Image inpainting can be roughly defined as: for an image containing missing regions, we want to fill the missing regions so that a visually plausible outcome is obtained. Image inpainting has developed very quickly and becomes one of the important contents of Digital Image Processing. Image inpainting can be employed in various applications, such as repairing aged images and multimedia editing. It is highly valuable in the protection of culture relic, movie and video special effect making .

Information theory is useful for finding the information content of the data which is referred to as Entropy. Microarray chip gives the data for gene expression. For finding co-expression between different genes generated from microarray, we have applied mutual information theory by finding entropy of each gene expression. This mutual information is converted into adjacency and dissimilarity matrix. Co-expressed networks are formed by applying cut- tree algorithm to dissimilarity matrix. Our work finds the pair wise relatedness of different microarray genes. This relatedness finds the different gene networks. We used the diabetes Mellitus Type II as a disease model. This paper describes our approach of finding co-expressed gene network .

The field of image retrieval has been an active research area for several decades and has been paid more and more attention in recent years as a result of the dramatic and fast increase in the volume of digital images. The developments of Internet not only cause an explosively growing volume of digital images, but also give people more ways to get those images. So, for this propose content based image retrieval system. Is a technique for retrieving images on the basis of derived features such as color, texture and shape. It will be helpful and easy way to retrieve image from huge database. In order to find image from huge database which uses dominant color it is image is uniformly divide into 8 coarse partition as a first step after above coarse partition, the centroid of each partition is selected dominant color .Texture of an image of an image is obtain by gray level Co-Occurrence matrix (GLCM) and as per shape concern we propose partial shape matching. Thus, using matching and comparison algorithms, the color, texture and shape features of one image are compared and matched to the corresponding features of another image. This comparison is performed using color, texture and shape distance metrics. In the end, these metrics are performed one after another, so as to retrieve database images that are similar to the query .

Image-data transmission from one site to another through public network is usually characterized in term of privacy, authenticity, and integrity. In this paper, we first describe a general scenario about how image is delivered from one site to another through a wide-area network (WAN) with security features of data privacy, integrity, and authenticity. Second, we give the common implementation method of the digital imaging and communication in medicine (DICOM) image communication software library with IPv6/IPv4 for high-speed broadband Internet by using open-source software. Third, we discuss two major security-transmission methods , the IP security (IPSec) and the secure-socket layer (SSL) or transport-layer security (TLS), being used currently in medical image- data communication with privacy support. Fourth, we describe a test schema of multiple-modality DICOM-image communications through TCP/IPv4 and TCP/IPv6 with different security methods, different security algorithms, and operating systems, and evaluate the test results. We found that there are tradeoff factors between choosing the IPsec and the SSL/TLS-based security implementation of IPv6/IPv4 protocols. If the WAN networks only use IPv6 such as in high-speed broadband Internet, the choice is IPsec-based security. If the networks are IPv4 or the combination of IPv6 and IPv4, it is better to use SSL/TLS security. The Linux platform has more security algorithms implemented than the Windows (XP) platform, and can achieve better performance in most experiments of IPv6 and IPv4-based DICOM-image communications. In teleradiology or enterprise-PACS applications, the Linux operating system may be the better choice as peer security gateways for both the IPsec and the SSL/TLS-based secure DICOM communications cross public networks.

Image segmentation has a long tradition as one of the fundamental problems in computer vision. Active contour models are widely used in image Segmentation problems. In these models, curves are evolved in an image from initial locations, in response to information derived from the image, to detect object boundaries , active contours that forces the level set function to be close to a signed distance function, and therefore completely eliminates the need of the costly re-initialization procedure and an external energy term that drives the motion of the zero level set toward the desired image features, such as object boundaries, represented by the zero level set of continuous level set functions. Instead, interfaces be represented by discontinuities of piecewise constant level set functions. Each level set function can at convergence only take two values, i.e., it can only be 1 or -1. The resulting evolution of the level set function minimizes the overall energy functional, thus the level set method is a versatile tool for tracing interfaces separating a domain into sub-domains.