This paper describes a method for image classification and retrieval for natural and urban scenes. The proposed algorithm is based on hierarchical image contents analysis. First image is classified as urban or natural according to color and edge distribution properties. Additionally scene is classified according to its conditions: illumination, weather, season and daytime based on contrast, sat...

This paper presents a universal blind steganalysis method for color images. The key new components of the presented method are color wavelet decomposition and a set of feature vectors. In addition, it is based on simple Fisher Linear Discriminatant approach for classifying the received image as containing steganographic content or not. The presented class of color wavelets has several useful pr...

This paper presents an approach to segment an image into areas of surfaces, and to compute the surface properties from a gray-scale image in order to describe the surfaces for reconstruction of the 3-D shape of the objects. At first edges are extracted from a gray-level image as many as possible. Next, the other characters of a surface (color, coordinates and image intensity) are extracted. The...

Microarray has emerged as a powerful technology that enables biologists to study thousands of genes simultaneously, therefore, to obtain a better understanding of the gene interaction and regulation mechanisms. This paper is concerned with improving the processes involved in the analysis of microarray image data. The main focus is to clarify an image's feature space in an unsupervised manner. I...

An approach to figure-ground segmentation based on a 2dimensional histogram in feature space is presented. The histogram is then analyzed with a peak-finding algorithm designed with real-time performance in mind. The most significant peaks in the histogram are backprojected to the image to produce an object mask. The method is applied to segmentation based on a 2-D color space and also on a com...

In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learning methods. At the low end of the hierarchy, the atomic motions (“letters”) corresponding to flow fields computed from successive color image frames are derived using Learning Vector Quantization (LVQ). At the next int...

Algorithms of Content-Based Image Retrieval (CBIR) have been well developed along with the explosion of information. These algorithms are mainly distinguished based on feature used to describe the image content. In this paper, the algorithms that are based on color feature and texture feature for image retrieval will be presented. Color Coherence Vector based image retrieval algorithm is also a...

land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

Detection of melanocytic skin lesion at an early stage increases the probability of being cured. Dermoscopy is a widely used diagnostic tool that aids the diagnosis of skin lesions and is proven to increase the accuracy of melanoma diagnosis. In this paper, vector based pattern analysis and classification approach for dermoscopic images are proposed. Feature plays a vital role in pattern recogn...

This paper describes the novel approach of feature extraction for CBIR systems. It also suggests the use of newly designed polynomial function to modify the image histogram so that the result of the CBIR system can be improved. To support this suggestion multiple polynomial functions have been tried. Out of which the best polynomial can be selected to modify the histogram for feature extraction...