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Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average. [ABSTRACT FROM AUTHOR]

Image splicing detection has been considered as one of the most challenging problems in passive image authentication. In this paper, we propose an automatic detection framework to identify a spliced image. Distinguishing from existing methods, the proposed system is based on a human visual system (HVS) model in which visual saliency and fixation are used to guide the feature extraction mechanism. An interesting and important insight of this work is that there is a high correlation between the splicing borders and the first few fixation points predicted by a visual attention model using edge sharpness as visual cues. We exploit this idea to develope a digital image splicing detection system with high performance. We present experimental results which show that the proposed system outperforms the prior arts. An additional advantage offered by the proposed system is that it provides a convenient way of localizing the splicing boundaries. [ABSTRACT FROM AUTHOR]

In this paper, we present a multiple representations and multiple queries approach to tackle the problem of invariance in the framework of content-based image retrieval (CBIR), especially in the case of texture. This approach, rather than considering invariance at the representation level, considers it at the query level. We use two models to represent texture visual content, namely the autoregressive model and a perceptual model based on a set of perceptual features. The perceptual model is used with two viewpoints: the original images viewpoint and the autocovariance function viewpoint. After a brief presentation and discussion of these multiple representation models / viewpoints, which are not invariant with respect to geometric and photometric transformations, we present the invariant texture retrieval algorithm, which is based on multiple models / viewpoints and multiple queries approach and consists in two levels of results fusion (merging): 1. The first level consists in merging results returned by the different models / viewpoints (representations) for the same query in one results list using a linear results fusion model; 2. The second level consists in merging each fused list of different queries into a unique fused list using a round robin fusion scheme. Experimentations show promising results. [ABSTRACT FROM AUTHOR]

In this paper we propose to revisit the well-known autoregressive model (AR) as a texture representation model. We consider the AR model with causal neighborhoods. First, we will define the AR model and discuss briefly the parameters estimation process. Then, we will present the synthesis algorithm and we will show some experimental results. The causal autoregressive model is applied in content-based image retrieval. Benchmarking conducted on the well-known Brodatz database shows interesting results. Both retrieval effectiveness (relevance) and retrieval efficiency are discussed and compared to the well-known multiresolution simultaneous autoregressive model (MRSAR). [ABSTRACT FROM AUTHOR]

In this paper we introduce the design, implementation and evaluation of the Dynamic Visualization Toolkit (DyVT) to support complex dynamic social network visualization. Dynamic aspects of social networks such as spatiotemporal as well as personalized information can be visualized in a common toolkit. To that end, an XML-based target language DyVTML is an extension of existing schemata enabling expression, storage and interchange of rich animated social network data. With the language and the available tool support, even less-experienced users can visualize temporal data in animations and spatial data in maps and personalize it with icons and colors. The prototype is evaluated by the visualization of large mailing list data sets. [ABSTRACT FROM AUTHOR]

In this paper we propose a method for detection of the car license plates in 2D gray images. In this method we first estimate the density of vertical edges in the image. The regions with high density vertical edges are good candidates for license plates. In order to filter out clutter regions possessing similar feature in the edge density image, we design a match filter which models the license plate pattern. By applying the proposed filter on the edge density image followed by a thresholding procedure, the locations of license plate candidates are detected. We finally extract the boundary of license plate(s) using the morphological operations. The result of experiments on car images (taken under different imaging conditions especially complex scenes) confirms the ability of the method for license plate detection. As the complexity of the proposed algorithm is low, it is considerably fast. [ABSTRACT FROM AUTHOR]

In this paper, we describe a visual language, based on the so-called Predicate Tree Metaphor, which allows users to visually build complex sentences for querying commonly used search engines. By using this visual language, no parentheses have to be applied, and no precedence rules have to be known. Promising results about the usability of the proposed interface are reported, on the basis on an experimental between-group study, performed on a Yahoo-based prototype of the proposed graphical environment. [ABSTRACT FROM AUTHOR]

Chorems are schematized representations of territories, and so they can represent a good visual summary of spatial databases. Indeed for spatial decision-makers, it is more important to identify and map problems than facts. Until now, chorems were made manually by geographers based on the own knowledge of the territory. So, an international project was launched in order to automatically discover spatial patterns and layout chorems starting from spatial databases. After examining some manually-made chorems some guidelines were identified. Then the architecture of a prototype system is presented based on a canonical database structure, a subsystem for spatial patterns discovery based on spatial data mining, a subsystem for chorem layout, and a specialized language to represent chorems. [ABSTRACT FROM AUTHOR]

In our project on the design of intelligent applications for an office environment we focus on the coffee corner as it is the place in an office where professional and social interactions intermingle. In this article the user-centered design of tangible interfaces, i.e. i-Candies and i-Bowl, which have been used as input devices to access company information in a coffee corner, is described. The i-Candies and the i-Bowl illustrate how everyday objects can be part of a context-aware system. By picking up one of the i-Candies and placing it on the i-Bowl, the i-Candy controls which information is presented on the wall display in the coffee corner. In our evaluation, we found that the office workers not only were enticed to interact with the i-Candies, but also that the i-Candies provided mediums that stimulate sociability among office workers. [ABSTRACT FROM AUTHOR]

Geometric modelling and haptic rendering of textiles is an area of research in which interest has significantly increased over the last decade. A haptic representation is created by adding the physical properties of an object to its geometric configuration. While research has been conducted into geometric modelling of fabrics, current systems require textile data to be manually entered into the computer simulation by a technician. This study explores the possibility of automatic generation of geometric and haptic models of real world textile samples. The development of a scalable and generic methodology for geometric and haptic modelling of plain weave textiles made from wool yarn is reported. This system has been successfully implemented using a step-wise procedure. Initially, an image of the textile artefact is captured. Then the critical features of the image are extracted from the image and deployed in a finite element model. The geometric model is augmented by adding physical properties of the textile and developing the haptic model. Two different haptic rendering procedures are implemented based on Reachin Application Programming Interface 3.2 (API). The developed methodologies are described and results obtained are provided. [ABSTRACT FROM AUTHOR]

In digital holography a CCD camera records optically generated holograms which is then reconstructed numerically by a calculation of scalar diffraction in the Fresnel approximation. The digital photography facilitates real time transmission of the message via traditional communication methods. In this paper the principle of digital holography and its application to the 3D image encryption-decryption are reviewed. The experimental results of firearm identification recording using digital holography and their numerical reconstruction are presented. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models. [ABSTRACT FROM AUTHOR]

In response to the need of using electronic design data directly in construction management applications, many CAD developers have started implementing semantic data models in their CAD products using industry foundation classes (IFCs). While helpful, these semantic CAD applications have limitations when used in actual construction practices. The case studies in the thesis indicated that: 1) the semantics of the current data model (IFC as an example) is not rich enough to cover the richer details of the real trade practices; 2) the current implementation of the semantic data model lacks the mechanism to provide multiple trades views at various detailed levels. This paper also provided suggestions for the future development of semantic data model of construction industry. [ABSTRACT FROM AUTHOR]

A Neurovision System can be defined as an artificial tool that sees our physical world. The purpose of this paper is to show a novel tool to design a 3D artificial vision system based on Resilient Neural Networks. Camera Calibration (CC) is a fundamental issue for Computational-Vision. Classical CC methods comprise of taking images of objects with known geometry, extracting the features of the objects from the images, and minimizing their 3D backprojection errors. In this paper, a novel implicit-CC model based on Resilient Neural Networks, CR, has been introduced. The CR is particularly useful for 3D reconstruction of the applications that do not require explicitly computation of physical camera parameters in addition to the expert knowledge. The CR supports intelligent-photogrammetry, photogrammetron. In order to evaluate the success of the proposed implicit-CC model, the 3D reconstruction performance of the CR has been compared with two different well-known implementations of the Direct Linear Transformation (DLT). The proposed method is also robust sufficiently for dealing with different cameras because it is capable of fusion of the image coordinates sourced from different cameras once the neural network has been trained. [ABSTRACT FROM AUTHOR]

Just-in-Time Information Retrieval (JITIR) systems aim to automatically retrieve useful information on the basis of the user's current task and to present this information to the user without disrupting that task. We ask whether the cognitive mechanism of ‘selective semantic processing' can minimise the disruptive nature of presenting JITIR information to the user. This mechanism may allow users to subconsciously filter out irrelevant information presented in the periphery of the visual field, while maintaining awareness of relevant information. We report an experiment assessing both attention to peripherally presented information (measured via recall) and level of distraction (measured via typing keystroke rate) in a JITIR system used to write reports on various topics. The experimental results showed that peripherally presented information that was relevant to a user's writing topic reliably entered their attention significantly more often than irrelevant information, and was significantly less distracting than similar but irrelevant information. [ABSTRACT FROM AUTHOR]

A geographic map is an important browsing tool for multimedia data that can include personal photos, but geographically correct maps are not always easy to use for that purpose due to the frequent zooming and panning, as well as the existence of extraneous information. This paper proposes a new user-interface concept for geo-tagged personal multimedia browsing in the form of a cognitive map. In addition, design criteria are defined and an auto-generation method is presented for this map. The proposed method produces a map represented as a clustered graph with vertices and edges in real time. It is visually compact, preserves geographical relationships among locations and is designed for both PCs and mobile devices. An experiment was conducted to test the proposed method with real-life data sets. [ABSTRACT FROM AUTHOR]

Automatic image annotation aims at labeling images with keywords. In this paper we investigate three annotation benchmark tasks used in literature to evaluate annotation systems' performance. We empirically compare the first two of the tasks, the 5000 Corel images and the Corel categories tasks, by applying a family of annotation system configurations derived from our PicSOM image content analysis framework. We establish an empirical correspondence of performance levels in the tasks by studying the performance of our system configurations, along with figures presented in literature. We also consider ImageCLEF 2006 Object Annotation Task that has earlier been found difficult. By experimenting with the data, we gain insight into the reasons that make the ImageCLEF task difficult. In the course of our experiments, we demonstrate that in these three tasks the PicSOM system—based on fusion of numerous global image features—outperforms the other considered annotation methods. [ABSTRACT FROM AUTHOR]