This paper presents our research in image content based indexing and retrieval, a key technology in digital image libraries. In most of the existing image content-based techniques, image features used for indexing and retrieval are global, features are computed over the entire image. The major problem with the global image feature based retrieval methods is that background features can be easil...

Current image indexing methods are based on measures of visual content. However, this approach provides only a partial solution to the image retrieval problem. For example, an artist might want to retrieve an image (for use in an advertising campaign) that evokes a particular “feeling” in the viewer. One technique for measuring evoked feelings, which originated in Japan, indexes images based on...

In this paper, we present a clustering-based color indexing scheme for effective amd efficient image retrieval, which is essentially an exploration on the application of clustering technique to image retrieval. In our approach, the color features are clustered automatically using a color clustering algorithm twice (called two-level clustering processing) and two color feature summarizations are...

| In content-based image indexing and retrieval, images are indexed based on the image attributes like, color, texture, shape. These attributes are used in enabling image retrieval based on query images. A user provides a sample image and the images in the database that are similar to the sample image are retrieved. Image content is represented in the form of feature vectors or histograms. In t...

OBJECTIVE To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. DESIGN The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and ...

We formulate the content-based image indexing problem as a multi-dimensional nearest-neighbor search problem, and develop/implement an optimistic vantage-point tree algorithm that can dynamically adapt the indexed search process to the characteristics of given queries. Based on our performance study, the system typically only needs to touch less than 20 % of the index entries for well -behaved ...

Given an image with N blocks of 8x8 pixels, we construct an indexing key by overlapping the N blocks into one combinational block and each block acting as one single plane inside the combinational block. Specific construction of each element inside the indexing key can have a range of alternatives based on such a common platform. These include: (i) average DCT value (ii) energy distributed in D...

The digitization of documents and their availability over the network demands solution toward content based document image analysis, indexing, searching and retrieval. Signature, Logo and Layout of the documents present convincing evidence and provide an important form of indexing for effective document image retrieval in a variety of applications. This paper describes methods and techniques de...

The use of the second order statistical measures has became popular in the image database indexing and retrieval. Unlike the common approach, image histogram, second order statistics like image correlogram and autocorrelogram consider also the spatial organization of the image colors or gray levels. Recently, correlograms and autocorrelograms have been widely used in the image database indexing...

We present a new approach to content-based image retrieval by addressing three primary issues: image indexing, similarity measure, and search methods. The proposed algorithms include: an image data warehousing structure for dynamic image indexing; a statistically based feature selection procedure to form flexible similarity measures in terms of the dominant image features; and a feature compone...