Content-based image retrieval from large multimedia databases effectively and efficiently is a challenging task. In this paper, we propose a retrieval technique that utilizes the regional properties of the images. After image segmentation, each region is represented by its colour, shape, size, and spatial position. Regions of different images are matched and a distance measure between the whole...

In this paper a prototype system is described for the management and content-based retrieval of defect images in huge image databases. This is a real problem in surface inspection applications, since modern inspection systems may produce up to thousands of defect images in a day. The retrieval is based on shape and internal structure characteristics of defects, so no manual labeling nor annotat...

In this paper, we present a novel algorithm for representing image content by constructing a hierarchy of semantic image regions, called a Semantic Segmentation Tree (SSeg-tree). First, the hill-manipulation algorithm divides an image into several visually coherent segments (small regions), which form the leaves of the SSeg-tree. Then, the method groups these segments based on well-defined spat...

Agent negotiation is a form of decision making where two or more agents jointly search for a mutually agreed solution to a certain problem. In multiissue negotiation, with information available about the agents’ preferences, a negotiation may result in a mutually beneficial agreement. In a competitive negotiation environment, however, self-interested agents may not be willing to reveal their pr...

This article provides a framework to describe and compare content-based image retrieval systems. Sixteen contemporary systems are described in detail, in terms of the following technical aspects: querying, relevance feedback, result presentation, features, and matching. For a total of 44 systems we list the features that are used. Of these systems, 35 use any kind of color features, 28 use text...

Relevance feedback methods for content-based image retrieval have shown promise in a variety of image database applications. These techniques assume two-class relevance feedback: relevant and irrelevant classes. While simple computationally, two-class relevance feedback often becomes inadequate in providing sufficient information to help rapidly improve retrieval performance. In this paper we p...

A new method for content-based image retrieval is being presented. This method uses a vector-space model to represent images in a multi-dimensional space. This model allows the use of multiple attributes in the retrieval process and also identiies the most selective values for each attribute. Therefore by ignoring the less signiicant values the user can reduce the dimensionality of the feature ...

This paper considered performance of content based image retrieval system using image representation nonparametric algorithms. Performance comparison of Epanechnikov, Gaussian and Histogram non-parametric algorithms was done in a generic image retrieval system. Chan & Vese and Cosine Angle Distance algorithms were used for segmentation and similarity matching respectively. The performance of th...

This paper presents a planar shape recognition method for content based image retrieval in multimedia databases. Shapes are characterised by their corners, which are extracted from the curvature function of their contours. Then, corner sequences are compared by using Hidden MarkovModels so that the process is resistant against corner shifting and loss. The proposed method has been successfully ...

We present a method for automatic textual annotation of compressed video. Initially, cuts are detected in the video sequence where consecutive frames show a large difference. Key frames are then extracted to represent each shot. A video sequence is, thus, condensed into a few images, hence this forms a compact key frame representation of the video. Each key frame is compared with an annotated d...