Automatic texture segmentation for texture-based image retrieval

Texture-segmentation is the crucial initial step for texture-based image retrieval. Texture is the main difficulty faced to a segmentation method. Many image segmentation algorithms either can’t handle texture properly or can’t obtain texture features directly during segmentation which can be used for retrieval purpose. This paper describes an automatic texture segmentation algorithm based on a set of features derived from wavelet domain, which are effective in texture description for retrieval purpose. Simulation results show that the proposed algorithm can efficiently capture the textured regions in arbitrary images, with the features of each region extracted as well. The features of each textured region can be directly used to index image database with applications as texture-based image retrieval.

Extraction of texture features from arbitrary-shaped regions for image retrieval

Lots of work has been done in texture feature extraction for rectangular images, but not as much attention has been paid to the arbitrary-shaped regions available in region-based image retrieval (RBIR) systems. In This work, we present a texture feature extraction algorithm, based on projection onto convex sets (POCS) theory. POCS iteratively concentrates more and more energy into the selected coefficients from which texture features of an arbitrary-shaped region can be extracted. Experimental results demonstrate the effectiveness of the proposed algorithm for image retrieval purposes.

Special issue: Selected papers from the sixth IFIP 2.6 working conference on visual database systems: Guest editors' introduction

While multimedia data, image data in particular, is an integral part of most websites and web documents, our quest for information so far is still restricted to text based search. To explore the World Wide Web more effectively, especially its rich repository of truly multimedia information, we are facing a number of challenging problems. Firstly, we face the ambiguous and highly subjective nature of defining image semantics and similarity. Secondly, multimedia data could come from highly diversified sources, as a result of automatic image capturing and generation processes. Finally, multimedia information exists in decentralised sources over the Web, making it difficult to use conventional content-based image retrieval (CBIR) techniques for effective and efficient search. In this special issue, we present a collection of five papers on visual and multimedia information management and retrieval topics, addressing some aspects of these challenges. These papers have been selected from the conference proceedings (Kluwer Academic Publishers, ISBN: 1-4020- 7060-8) of the Sixth IFIP 2.6 Working Conference on Visual Database Systems (VDB6), held in Brisbane, Australia, on 29–31 May 2002.

Hierarchical indexing structure for efficient similarity search in video retrieval

With the rapid increase in both centralized video archives and distributed WWW video resources, content-based video retrieval is gaining its importance. To support such applications efficiently, content-based video indexing must be addressed. Typically, each video is represented by a sequence of frames. Due to the high dimensionality of frame representation and the large number of frames, video indexing introduces an additional degree of complexity. In this paper, we address the problem of content-based video indexing and propose an efficient solution, called the Ordered VA-File (OVA-File) based on the VA-file. OVA-File is a hierarchical structure and has two novel features: 1) partitioning the whole file into slices such that only a small number of slices are accessed and checked during k Nearest Neighbor (kNN) search and 2) efficient handling of insertions of new vectors into the OVA-File, such that the average distance between the new vectors and those approximations near that position is minimized. To facilitate a search, we present an efficient approximate kNN algorithm named Ordered VA-LOW (OVA-LOW) based on the proposed OVA-File. OVA-LOW first chooses possible OVA-Slices by ranking the distances between their corresponding centers and the query vector, and then visits all approximations in the selected OVA-Slices to work out approximate kNN. The number of possible OVA-Slices is controlled by a user-defined parameter delta. By adjusting delta, OVA-LOW provides a trade-off between the query cost and the result quality. Query by video clip consisting of multiple frames is also discussed. Extensive experimental studies using real video data sets were conducted and the results showed that our methods can yield a significant speed-up over an existing VA-file-based method and iDistance with high query result quality. Furthermore, by incorporating temporal correlation of video content, our methods achieved much more efficient performance.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

A synchronous multimedia annotation system for secure collaboratories

In this paper, we describe the Vannotea system - an application designed to enable collaborating groups to discuss and annotate collections of high quality images, video, audio or 3D objects. The system has been designed specifically to capture and share scholarly discourse and annotations about multimedia research data by teams of trusted colleagues within a research or academic environment. As such, it provides: authenticated access to a web browser search interface for discovering and retrieving media objects; a media replay window that can incorporate a variety of embedded plug-ins to render different scientific media formats; an annotation authoring, editing, searching and browsing tool; and session logging and replay capabilities. Annotations are personal remarks, interpretations, questions or references that can be attached to whole files, segments or regions. Vannotea enables annotations to be attached either synchronously (using jabber message passing and audio/video conferencing) or asynchronously and stand-alone. The annotations are stored on an Annotea server, extended for multimedia content. Their access, retrieval and re-use is controlled via Shibboleth identity management and XACML access policies.

Indexing and integrating multiple features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

Dormancy release in Lolium rigidum seeds is a function of thermal after-ripening time and seed water content

Dormancy release in seeds of Lolium rigidum Gaud. (annual ryegrass) was investigated in relation to temperature and seed water content. Freshly matured seeds were collected from cropping fields at Wongan Hills and Merredin, Western Australia. Seeds from Wongan Hills were equilibrated to water contents between 6 and 18% dry weight and after-ripened at constant temperatures between 9 and 50degreesC for up to 23 weeks. Wongan Hills and Merredin seeds at water contents between 7 and 17% were also after-ripened in full sun or shade conditions. Dormancy was tested at regular intervals during after-ripening by germinating seeds on agar at 12-h alternating 15degreesC (dark) and 25degreesC (light) periods. Rate of dormancy release for Wongan Hills seeds was a positive linear function of after-ripening temperature above a base temperature (T-b) of 5.4degreesC. A thermal after-ripening time model for dormancy loss accounting for seed moisture in the range 6-18% was developed using germination data for Wongan Hills seeds after-ripened at constant temperatures. The model accurately predicted dormancy release for Wongan Hills seeds after-ripened under naturally fluctuating temperatures. Seeds from Merredin responded similarly but had lower dormancy at collection and a faster rate of dormancy release in seeds below 9% water content.

Cationic drug pharmacokinetics in diseased livers determined by fibrosis index, hepatic protein content, microsomal activity, and nature of drug

The disposition kinetics of six cationic drugs in perfused diseased and normal rat livers were determined by multiple indicator dilution and related to the drug physicochemical properties and liver histopathology. A carbon tetrachloride (CCl4)induced acute hepatocellular injury model had a higher fibrosis index (FI), determined by computer-assisted image analysis, than did an alcohol-induced chronic hepatocellular injury model. The alcohol-treated group had the highest hepatic alpha(1)- acid glycoprotein, microsomal protein (MP), and cytochrome P450 (P450) concentrations. Various pharmacokinetic parameters could be related to the octanol-water partition coefficient (log P-app) of the drug as a surrogate for plasma membrane partition coefficient and affinity for MP or P450, the dependence being lower in the CCl4-treated group and higher in the alcohol-treated group relative to controls. Stepwise regression analysis showed that hepatic extraction ratio, permeability-surface area product, tissue-binding constant, intrinsic clearance, partition ratio of influx (k(in)) and efflux rate constant (k(out)), and k(in)/k(out) were related to physicochemical properties of drug (log P-app or pK(a)) and liver histopathology (FI, MP, or P450). In addition, hepatocyte organelle ion trapping of cationic drugs was evident in all groups. It is concluded that fibrosis-inducing hepatic disease effects on cationic drug disposition in the liver may be predicted from drug properties and liver histopathology.

Codon usage bias and A+T content variation in human papillomavirus genomes

We analyzed the codon usage bias of eight open reading frames (ORFs) across up to 79 human papillomavirus (HPV) genotypes from three distinct phylogenetic groups. All eight ORFs across HPV genotypes show a strong codon usage bias, amongst degenerately encoded amino acids, toward 18 codons mainly with T at the 3rd position. For all 18 degenerately encoded amino acids, codon preferences amongst human and animal PV ORFs are significantly different from those averaged across mammalian genes. Across the HPV types, the L2 ORFs show the highest codon usage bias (73.2 +/- 1.6% and the E4 ORFs the lowest (51.1 +/- 0.5%), reflecting as similar bias in codon 3rd position A + T content (L2: 76.1 +/- 4.2%; E4: 58.6 +/- 4.5%). The E4 ORF, uniquely amongst the HPV ORFs, is G + C rich, while the other ORFs are A + T rich. Codon usage bias correlates positively with A + T content at the codon 3rd position in the E2, E6, L1 and L2 ORFs, but negatively in the E4 ORFs. A general conservation of preferred codon usage across human and non-human PV genotypes whether they originate from a same supergroup or not, together with observed difference between the preferred codon usage for HPV ORFs and for genes of the cells they infect, suggests that specific codon usage bias and A + T content variation may somehow increase the replicational fitness of HPVs in mammalian epithelial cells, and have practical implications for gene therapy of HPV infection. (C) 2003 Elsevier B.V. All rights reserved.

Document retrieval for e-mail search and discovery using Formal Concept Analysis

This paper discusses a document discovery tool based on Conceptual Clustering by Formal Concept Analysis. The program allows users to navigate e-mail using a visual lattice metaphor rather than a tree. It implements a virtual. le structure over e-mail where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in e-mail discovery. The system described provides more flexibility in retrieving stored e-mails than what is normally available in e-mail clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.