In this paper, a new algorithm for content− based image indexing and retrieval is presented. The proposed method is based on a combination of multiresolution analysis and color correlation histogram of the image. According to the new algorithm, wavelet coefficients of the image are computed first using Daubechies wavelets. A quantization step is then applied before computing horizontal and vert...

Medical images need to be transmitted with the patient's information without altering the image data. The present paper discusses secured indexing of lung CT image (SILI) which is a secured way of indexing the lung CT images with the patient information. Authentication is provided using the sender's logo information and the secret key is used for embedding the watermark into the host image. Wat...

Visual data such as videos and images play an important role in medical diagnosis and training. The ability to express spatial and visual queries and to search for relevant visual information from image archives poses a major challenge for the development of advanced image indexing. Searching technologies must not only be robust but also be capable of scaling up to large collections across wide...

Digitization has created an abundance of new information sources by altering how pictures are captured. Accessing large image databases from a web portal requires opted indexing structure instead reducing the contents different kinds for quick processing. This approach paves path toward increase efficient retrieval techniques and numerous research in involving datasets. Image usually encounters...

Managing the ever rapidly increasing image data is a very challenging task, which can be roughly divided into user side and computer side issues. Although fundamental problems on the computer side of the challenge, such as image content representation, similarity matching and intelligent retrieval have received extensive research effort, equally important and difficult issues on the user side, ...

Most existing image indexing techniques rely on Scale Invariant Feature Transformation (SIFT) for extracting local point features. Applied to individual image, SIFT extracts hundreds of numerical vectors. The vectors are quantized and stored in tree-like data structures for fast search. SIFTbased indexing can exhibit weakness under certain non-rigid transformations, which are common among real ...

This paper is concerned with the indexing and retrieval of images based on features extracted directly from the JPEG discrete cosine transform (DCT) domain. We examine possible ways of manipulatingDCT coe$cients by standard image analysis approaches to describe image shape, texture, and color. Through the Mandala transformation, our approach groups a subset of DCT coe$cients to form ten blocks....