An Image with high-resolution is associated huge size data space because each information of the image arranged into 2D picture elements' values, them containing its value RGB bits. The depiction makes it challenging to distribute files using Internet. For Internet users, time takes upload and download photos has all been main concern. A up more storage space, in addition transit difficulty. An...

Background: Body image is an integral component of the self-concept that significantly shapes human functioning and people’s life outcomes. Although negative body image is well-studied, there is little research on positive body image. The study examined the basic characteristics of positive body image intending to standardize a scale for it.  Methods: The study used using an exploratory resear...

This paper presents a new robust watermarking scheme for color image based on Partial Differential Equations (PDE). Specifically, the mark is inserted in to texture component obtained after decomposition of the image by PDE. The watermark used is a binary matrix for the texture component. Experimentation has ensured the mark invisibility, the facility of detection of the mark and the robustness...

The novel approach to the image sharpening problem is proposed in this paper. It is based on the application of the independent component analysis (ICA) algorithm on the image sequence with the appropriate time displacement between the image frames. The novelty is in the data representation required by the ICA algorithms where each selected image frame has been used as a sensor implying that un...

The parallel watershed transformation used in grayscale image segmentation is reconsidered in this paper on the basis of the component labeling problem. The main idea is to break the sequentiality of the watershed transformation and to correctly delimit the extent of all connected components locally, on each processor, simultaneously. The internal fragmentation of the catchment basins, due to d...

Jake K. Aggarwal University of Texas at Austin Department of Electrical and Computer Engineering Computer Vision Research Center Austin, Texas 78712-1084 Abstract. An important step in target acquisition is to be able to label various unconnected objects (components) in the scene. We present new algorithms for labeling connected components in a binary image. Eight connectivity for object and ba...

This paper addresses the problem of image categorization using local sensory information which is aggregated into global cortical-like representations of diierent image categories. Local information is adaptively extracted from an image database using Independent Component Analysis (ICA) which provides a set of localized, oriented, and band-pass lters selective to independent features of the di...

We present a novel quantum algorithm for the classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements. In order to apply the algorithm we present a new quantum representation of grayscale images.

Segmentation of Grey/White/CSF from MR images depends on contrast to noise ratios (CNR) among these tissues and the CSF. The CNRs are determined by the acquisition method and imaging parameters. These factors can be optimized for improved image segmentation [1,21. In many MR studies, multiple images of the same slice locations are acquired, each with different weightings based Tl/T2/proton dens...

The availability of hyperspectral images expands the capability of using image classification to study detailed characteristics of objects, but at a cost of having to deal with huge data sets. This work studies the use of the principal component analysis as a preprocessing technique for the classification of hyperspectral images. Two hyperspectral data sets, HYDICE and AVIRIS, were used for the...