Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

Image mining: issues, frameworks and techniques

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. Despite the development of many applications and algorithms in the individual research fields cited above, research in image mining is still in its infancy. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining at the end of this paper

Visual Information Retrieval in Digital Libraries

The emergence of information highways and multimedia computing has resulted in redefining the concept of libraries. It is widely believed that in the next few years, a significant portion of information in libraries will be in the form of multimedia electronic documents. Many approaches are being proposed for storing, retrieving, assimilating, harvesting, and prospecting information from these multimedia documents. Digital libraries are expected to allow users to access information independent of the locations and types of data sources and will provide a unified picture of information. In this paper, we discuss requirements of these emerging information systems and present query methods and data models for these systems. Finally, we briefly present a few examples of approaches that provide a preview of how things will be done in the digital libraries in the near future.published or submitted for publicatio

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Image databases: Problems and perspectives

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined

Applying contextual memory cues for retrieval from personal information archives

Advances in digital technologies for information capture combined with massive increases in the capacity of digital storage media mean that it is now possible to capture and store one’s entire life experiences in a Human Digital Memory (HDM). Information can be captured from a myriad of personal information devices including desktop computers, PDAs, digital cameras, video and audio recorders, and various sensors, including GPS, Bluetooth, and biometric devices. These diverse collections of personal information are potentially very valuable, but will only be so if significant information can be reliably retrieved from them. HDMs differ from traditional document collections for which existing search technologies have been developed since users may have poor recollection of contents or even the existence of stored items. Additionally HDM data is highly heterogeneous and unstructured, making it difficult to form search queries. We believe that a Personal Information Management (PIM) system which exploits the context of information capture, and potentially of earlier refinding, can be valuable in effective retrieval from an HDM. We report an investigation into how individuals perform searches of their personal information, and use the outcome of this study to develop an information retrieval (IR) framework for HDM search incorporating the context of document capture. We then describe the creation of a pilot HDM test collection, and initial experiments in retrieval from this collection. Results from these experiments indicate that use of context data can be significantly beneficial to increasing the efficient retrieval of partially recalled items from an HDM

Content And Multimedia Database Management Systems

A database management system is a general-purpose software system that facilitates the processes of defining, constructing, and manipulating databases for various applications. The main characteristic of the ‘database approach’ is that it increases the value of data by its emphasis on data independence. DBMSs, and in particular those based on the relational data model, have been very successful at the management of administrative data in the business domain. This thesis has investigated data management in multimedia digital libraries, and its implications on the design of database management systems. The main problem of multimedia data management is providing access to the stored objects. The content structure of administrative data is easily represented in alphanumeric values. Thus, database technology has primarily focused on handling the objects’ logical structure. In the case of multimedia data, representation of content is far from trivial though, and not supported by current database management systems

Indexing Techniques for Image and Video Databases: an approach based on Animate Vision Paradigm

[ITALIANO]In questo lavoro di tesi vengono presentate e discusse delle innovative tecniche di indicizzazione per database video e di immagini basate sul paradigma della “Animate Vision” (Visione Animata). Da un lato, sarà mostrato come utilizzando, quali algoritmi di analisi di una data immagine, alcuni meccanismi di visione biologica, come i movimenti saccadici e le fissazioni dell'occhio umano, sia possibile ottenere un query processing in database di immagini più efficace ed efficiente. In particolare, verranno discussi, la metodologia grazie alla quale risulta possibile generare due sequenze di fissazioni, a partire rispettivamente, da un'immagine di query I_q ed una di test I_t del data set, e, come confrontare tali sequenze al fine di determinare una possibile misura della similarità (consistenza) tra le due immagini. Contemporaneamente, verrà discusso come tale approccio unito a tecniche classiche di clustering possa essere usato per scoprire le associazioni semantiche nascoste tra immagini, in termini di categorie, che, di contro, permettono un'automatica pre-classificazione (indicizzazione) delle immagini e possono essere usate per guidare e migliorare il processo di query. Saranno presentati, infine, dei risultati preliminari e l'approccio proposto sarà confrontato con le più recenti tecniche per il recupero di immagini descritte in letteratura. Dall'altro lato, sarà mostrato come utilizzando la precedente rappresentazione “foveata” di un'immagine, risulti possibile partizionare un video in shot. Più precisamente, il metodo per il rilevamento dei cambiamenti di shot si baserà sulla computazione, in ogni istante di tempo, della misura di consistenza tra le sequenze di fissazioni generate da un osservatore ideale che guarda il video. Lo schema proposto permette l'individuazione, attraverso l'utilizzo di un'unica tecnica anziché di più metodi dedicati, sia delle transizioni brusche sia di quelle graduali. Vengono infine mostrati i risultati ottenuti su varie tipologie di video e, come questi, validano l'approccio proposto. / [INGLESE]In this dissertation some novel indexing techniques for video and image database based on “Animate Vision” Paradigm are presented and discussed. From one hand, it will be shown how, by embedding within image inspection algorithms active mechanisms of biological vision such as saccadic eye movements and fixations, a more effective query processing in image database can be achieved. In particular, it will be discussed the way to generate two fixation sequences from a query image I_q and a test image I_t of the data set, respectively, and how to compare the two sequences in order to compute a possible similarity (consistency) measure between the two images. Meanwhile, it will be shown how the approach can be used with classical clustering techniques to discover and represent the hidden semantic associations among images, in terms of categories, which, in turn, allow an automatic pre-classification (indexing), and can be used to drive and improve the query processing. Eventually, preliminary results will be presented and the proposed approach compared with the most recent techniques for image retrieval described in the literature. From the other one, it will be discussed how by taking advantage of such foveated representation of an image, it is possible to partitioning of a video into shots. More precisely, the shot-change detection method will be based on the computation, at each time instant, of the consistency measure of the fixation sequences generated by an ideal observer looking at the video. The proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. Results on videos of various content types are reported and validate the proposed approach

Image indexing and retrieval: some problems and proposed solutions.

Image processing technologies are offering considerable potential for library and information units to extend their databases by the inclusion of images such as photographs, paintings, monograph title-pages and maps. Discusses problems and potential solutions in a structured fashion based on categories of thesauri (text and visual), hybrids, description language and automatic content analysis, with state-of-the-art examples