The estimation of the posterior class probabilities is desirable for optimal decision, decision confidence measure, and accurate performance evaluation of a classifier. In this paper, we address the problem of estimating posterior class probabilities by learning from samples for producing optimal classifiers. We introduce a posterior pseudo-probability function based on Bayes’ formula to transf...

Analyzing the limitations which exist in content-based image retrieval (CBIR) systems on optimization model, generalization design and retrieval efficiency, a combinative model based on image features correlation retrieval is designed, using some proper algorithms of image retrieval, relevance feedback principle and the advantage of DSP chip in image signal processing. The work mode is useful f...

While image segmentation makes up a vital step in the process of such tasks in the medical domain as tissue classification, content-based image retrieval, and computer-aided diagnosis, it remains an area of much debate regarding how one interprets the results of machine segmented regions. Many segmentation methods are still evaluated using a subjective human opinion of quality with a lack of qu...

Choosing test cases for the optimization process of information systems testing is crucial, because it helps to eliminate unnecessary and redundant testing data. However, its use in systems that address complex domains (e.g. images) is still underexplored. This paper presents a new approach that uses Content-Based Image Retrieval (CBIR), similarity functions and clustering techniques to select ...

Performance evaluation of content-based image retrieval (CBIR) systems is an important but still unsolved problem. The reason for its importance is that only performance evaluation allows for comparison and integration of different CBIR systems. We propose an image retrieval system that splits the retrieval process into two stages. Users are querying the system through image description using a...

In order to utilize the large volume of images in databases efficiently, content-based image retrieval (CBIR) has been successfully employed whereby instead of the actual images extracted feature descriptors are used. CBIR systems usually employ multidimensional indexing structures, such as the R*tree or the SR-tree to index these features and thus to speed-up the query performance. However, th...

In this chapter, we present a basic introduction of the two very important areas of research in the domain of information technology, namely, multimedia systems and content-based image retrieval. The latter is still a widely unresolved problem. We discuss some of the works done so far in content-based image retrieval in the context of multimedia systems.

The paper discusses the role of invariance in content-based image retrieval, and discusses future directions.