The DICEMAN description schemes for still images and video sequences

To address the problem of visual content description, two Description Schemes (DSs) developed within the context of a European ACTS project known as DICEMAN, are presented. The DSs, designed based on an analogy with well-known tools for document description, describe both the structure and semantics of still images and video sequences. The overall structure of both DSs including the various sub-DSs and descriptors (Ds) of which they are composed is described. In each case, the hierarchical sub-DS for describing structure can be constructed using automatic (or semi-automatic) image/video analysis tools. The hierarchical sub-DSs for describing the semantics, however, are constructed by a user. The integration of the two DSs into a video indexing application currently under development in DICEMAN is also briefly described.Peer ReviewedPostprint (published version

Study of the urban evolution of Brasilia with the use of LANDSAT data

The urban growth of Brasilia within the last ten years is analyzed with special emphasis on the utilization of remote sensing orbital data and automatic image processing. The urban spatial structure and the monitoring of its temporal changes were focused in a whole and dynamic way by the utilization of MSS-LANDSAT images for June 1973, 1978 and 1983. In order to aid data interpretation, a registration algorithm implemented at the Interactive Multispectral Image Analysis System (IMAGE-100) was utilized aiming at the overlap of multitemporal images. The utilization of suitable digital filters, combined with the images overlap, allowed a rapid identification of areas of possible urban growth and oriented the field work. The results obtained permitted an evaluation of the urban growth of Brasilia, taking as reference the proposed stated for the construction of the city

DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structure. In this paper, we propose an automatic feature discovery framework for extracting discriminative class-specific features and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific features which are suitable for representing samples from the same class while are poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian lung images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, show the significance of DFDL model in a variety problems over state-of-the-art methodsComment: Accepted to IEEE International Symposium on Biomedical Imaging (ISBI), 201

The impact of the image resolution on the value of measured geometric parameters on the example of ductile iron structure

Paper presents the influence of the image resolution on measurement geometric parameters of the objects. Employing as test images the ductile iron structure images allow to analyze the effect of resolution distortion on a model of objects with regular shape. Authors showed on the example images, how decreasing resolution of digital images distorts the value of the parameters describing the shape of the objects, its perimeter and its quantity. The analysis was performed by an automatic algorithm applying image analysis and stereological method

Segmentasi Citra Secara Semi-otomatis Untuk Visualisasi Volumetrik Citra Ct-scan Pelvis

Semi-Automatic Image Segmentation for Volumetric Visualization of Pelvis CT Scan-Images. The currentdevelopment of computerized tomography (CT) has enable us to obtain cross sectional image using multi slicingtechniques in an order of few seconds. The obtained images represent several tissue structures on cross section slicebeing imaged. One challenge to help diagnosis using CT images is extracting an anatomic structure of interest using amethod of image segmentation and volumetric visualization with the assistance of computers. In case of volumetricvisualization of pelvis bones extracted from multi-slice CT images, whole images which are containing part of pelvisbone structures must be segmented. In this research, an image segmentation technique based on active contour isimplemented for semi-automatic multi slice image segmentation. Image segmentation steps are initialized with a definemodel of 2D curve on the first slice image manually. Next, its model curve is deformed to reach the final result of 2Dcurve that fits to boundary edges of pelvis bone image. The final result of 2D curve on previous slice image was used asan initialization model of 2D curve on the next slice images. This process will continue until the final slice image. Thissegmentation method was compared with the segmentation method based on threshold from homogenous intensitydistribution and manual segmentation method. Quantitative analysis from the results of segmentation on each slice andqualitative analysis on the representation of volumetric visualization are performed in this research

IMAGE SYNTHESIS OF METAL FOAM MICRO-STRUCTURE WITH THE USE OF WANG TILES

In this paper we present our recent work focused on the analysis of the abilities of Wang Tiles method and Automatic tile design method to synthesize the micro-structure of cellular materials, especially particular type of metal foam.Wang Tiles method stores and compress the micro-structure in a set of Wang Tiles and by the means of stochastic tiling algorithms the planar domain is reconstructed. The used tiles are created by the Automatic tile design method from respective number of small specimens extracted from the original micro-structure image. As an additional step the central areas of automatically designed tiles are patched to suppress the influence of repeating tile edges (and relevant tile quarters) on inducing artifacts. In the presented analysis the performance of raw and patched tiles of different sizes in conjunction of various tile sets is investigated

Image Captioning through Image Transformer

Automatic captioning of images is a task that combines the challenges of image analysis and text generation. One important aspect in captioning is the notion of attention: How to decide what to describe and in which order. Inspired by the successes in text analysis and translation, previous work have proposed the \textit{transformer} architecture for image captioning. However, the structure between the \textit{semantic units} in images (usually the detected regions from object detection model) and sentences (each single word) is different. Limited work has been done to adapt the transformer's internal architecture to images. In this work, we introduce the \textbf{\textit{image transformer}}, which consists of a modified encoding transformer and an implicit decoding transformer, motivated by the relative spatial relationship between image regions. Our design widen the original transformer layer's inner architecture to adapt to the structure of images. With only regions feature as inputs, our model achieves new state-of-the-art performance on both MSCOCO offline and online testing benchmarks

Strategies for image visualisation and browsing

PhDThe exploration of large information spaces has remained a challenging task even though the proliferation of database management systems and the state-of-the art retrieval algorithms is becoming pervasive. Signi cant research attention in the multimedia domain is focused on nding automatic algorithms for organising digital image collections into meaningful structures and providing high-semantic image indices. On the other hand, utilisation of graphical and interactive methods from information visualisation domain, provide promising direction for creating e cient user-oriented systems for image management. Methods such as exploratory browsing and query, as well as intuitive visual overviews of image collection, can assist the users in nding patterns and developing the understanding of structures and content in complex image data-sets. The focus of the thesis is combining the features of automatic data processing algorithms with information visualisation. The rst part of this thesis focuses on the layout method for displaying the collection of images indexed by low-level visual descriptors. The proposed solution generates graphical overview of the data-set as a combination of similarity based visualisation and random layout approach. Second part of the thesis deals with problem of visualisation and exploration for hierarchical organisation of images. Due to the absence of the semantic information, images are considered the only source of high-level information. The content preview and display of hierarchical structure are combined in order to support image retrieval. In addition to this, novel exploration and navigation methods are proposed to enable the user to nd the way through database structure and retrieve the content. On the other hand, semantic information is available in cases where automatic or semi-automatic image classi ers are employed. The automatic annotation of image items provides what is referred to as higher-level information. This type of information is a cornerstone of multi-concept visualisation framework which is developed as a third part of this thesis. This solution enables dynamic generation of user-queries by combining semantic concepts, supported by content overview and information ltering. Comparative analysis and user tests, performed for the evaluation of the proposed solutions, focus on the ways information visualisation a ects the image content exploration and retrieval; how e cient and comfortable are the users when using di erent interaction methods and the ways users seek for information through di erent types of database organisation