Digital images are useful media for storing spatial, spectral and temporal components of information. Large image databases often store the images in compressed format, JPEG for example. This paper examines the algorithms of direct extraction of low level features from compressed images, working with three different clustering techniques. Results indicate that a K-Harmonic means clustering algo...

In this paper we consider how information may be obtained from images. To search large image collections we need to search on secondary parameters. We may look for images containing certain types of objects, for images where the objects are of a certain size or shape, or for images having certain features. Since we now have techniques to rapidly acquire and store many images, we need techniques...

Similar images are images with common features, similar pixel distributions, and similar edge distributions. Fields such as medical imaging or satellite imaging often need to store large collections of similar images. In a set of similar images the image similarities represent patterns that consistently appear across all images; this results in “set redundancy”. This paper presents the Centroid...

The Problem: The goal of low-level vision is to estimate an underlying scene (e.g., albedos or shapes), given an observed image. Real-world scenes can be very complex, conventionally requiring high dimensional representations that are hard to estimate and store. In this work, we propose a low-dimensional representation, called a scene recipe, that relies on the image itself to describe the comp...

We investigate transform coding to efficiently store and transmit SIFT and SURF image descriptors. We show that image and feature matching algorithms are robust to significantly compressed features. We achieve nearperfect image matching and retrieval for both SIFT and SURF using ∼2 bits/dimension. When applied to SIFT and SURF, this provides a 16× compression relative to conventional floating p...

Many Smalltalk implementations store objects in a large file called a virtual image. Each user must have a copy of the virtual image to execute. Since the image can exceed a megabyte in size, considerable disk space is required to support such a system in a multi-user environment. In this paper, a method is described which can reduce storage requirements for systems which use generation scaveng...