The theory of images in the representation of functions.

Thesis (Ph.D.)--Cornell University, 1888.

Recursive filtering of images with symmetric extension

Recursive filters are widely used in image analysis due to their efficiency and simple implementation. However these filters have an initialisation problem which either produces unusable results near the image boundaries or requires costly approximate solutions such as extending the boundary manually. In this paper, we describe a method for the recursive filtering of symmetrically extended images for filters with symmetric denominator. We begin with an analysis of symmetric extensions and their effect on non-recursive filtering operators. Based on the non-recursive case, we derive a formulation of recursive filtering on symmetric domains as a linear but spatially varying implicit operator. We then give an efficient method for decomposing and solving the linear implicit system, along with a proof that this decomposition always exists. This decomposition needs to be performed only once for each dimension of the image. This yields a filtering which is both stable and consistent with the ideal infinite extension. The filter is efficient, requiring less computation than the standard recursive filtering. We give experimental evidence to verify these claims. (c) 2005 Elsevier B.V. All rights reserved.

Neural-Like Growing Networks in Intelligent System of Recognition of Images

The neural-like growing networks used in the intelligent system of recognition of images are under consideration in this paper. All operations made over the image on a pre-design stage and also classification and storage of the information about the images and their further identification are made extremely by mechanisms of neural-like networks without usage of complex algorithms requiring considerable volumes of calculus. At the conforming hardware support the neural network methods allow considerably to increase the effectiveness of the solution of the given class of problems, saving a high accuracy of result and high level of response, both in a mode of training, and in a mode of identification.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

A contribution to semantic description of images and videos: an application of soft biometrics

Humans have a high ability to extract visual data information acquired by sight. Trought a learning process, which starts at birth and continues throughout life, image interpretation becomes almost instinctively. At a glance, one can easily describe a scene with reasonable precision, naming its main components. Usually, this is done by extracting low-level features such as edges, shapes and textures, and associanting them to high level meanings. In this way, a semantic description of the scene is done. An example of this, is the human capacity to recognize and describe other people physical and behavioral characteristics, or biometrics. Soft-biometrics also represents inherent characteristics of human body and behaviour, but do not allow unique person identification. Computer vision area aims to develop methods capable of performing visual interpretation with performance similar to humans. This thesis aims to propose computer vison methods which allows high level information extraction from images in the form of soft biometrics. This problem is approached in two ways, unsupervised and supervised learning methods. The first seeks to group images via an automatic feature extraction learning , using both convolution techniques, evolutionary computing and clustering. In this approach employed images contains faces and people. Second approach employs convolutional neural networks, which have the ability to operate on raw images, learning both feature extraction and classification processes. Here, images are classified according to gender and clothes, divided into upper and lower parts of human body. First approach, when tested with different image datasets obtained an accuracy of approximately 80% for faces and non-faces and 70% for people and non-person. The second tested using images and videos, obtained an accuracy of about 70% for gender, 80% to the upper clothes and 90% to lower clothes. The results of these case studies, show that proposed methods are promising, allowing the realization of automatic high level information image annotation. This opens possibilities for development of applications in diverse areas such as content-based image and video search and automatica video survaillance, reducing human effort in the task of manual annotation and monitoring.

Pretest of images associated with the expertise dimension

In this paper, we present norms concerning the perceived association that two sets of stimuli (photos of people and photos of objects) establish with the concept of expertise. Participants were presented with a set of words associated with the expertise dimension and subsequently asked to judge each stimulus on how much it related with the learned (expertise) dimension on a 7-point scale (1 – Not at all related; 7 – Very related). The interpretation of means’ confidence intervals allowed us to distinguish between images highly related with the expertise dimension and images highly unrelated with this dimension. Summarized results are presented and photos made available to support future research requiring stimuli associated with the expertise dimension.

Sistema de captação de imagens para avaliação dos movimentos biomecânicos das articulações temporomandibulares

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Design of a Web interface for anatomical images

Interactive documents for use with the World Wide Web have been developed for viewing multi-dimensional radiographic and visual images of human anatomy, derived from the Visible Human Project. Emphasis has been placed on user-controlled features and selections. The purpose was to develop an interface which was independent of host operating system and browser software which would allow viewing of information by multiple users. The interfaces were implemented using HyperText Markup Language (HTML) forms, C programming language and Perl scripting language. Images were pre-processed using ANALYZE and stored on a Web server in CompuServe GIF format. Viewing options were included in the document design, such as interactive thresholding and two-dimensional slice direction. The interface is an example of what may be achieved using the World Wide Web. Key applications envisaged for such software include education, research and accessing of information through internal databases and simultaneous sharing of images by remote computers by health personnel for diagnostic purposes.

Using images to communicate the hidden struggles of life on dialysis

Background: Nurse-patient communication in the hemodialysis context is unique given the amount of time spent together in a confined clinical room. Poor communication may lead to low quality nursing care and undesirable patient outcomes. Aim: To explore the use of images as a visual communication technique for nurses and patients in the hemodialysis context. Methods: Descriptive qualitative design. Fifty two cards containing specific photos, illustrations and words were used in conversations between patients (n = 9) and one of two nurse interviewers about being on hemodialysis. Interview transcripts were thematically analysed. Findings: An overall theme titled ‘revealing the hidden struggles of living on dialysis’ conceptually captured three sub-themes: (1) the increased importance of relationships; (2) the struggle with money; and (3) quality over quantity of life. The cards assisted in uncovering these often covert (to nurses) aspects of dialysis patients’ lives. Conclusion: Nurses may need to be aware of the dialysis patients’ hidden struggles which include the importance of relationships, financial issues and the importance of quality aspects such as travel. The use of images may assist in revealing the important issues for each patient struggling with the restrictive life that is imposed by dialysis.

The visibility of disaster deaths in news images : a comparison of newspapers from 15 countries

The extent to which newspapers display graphic images of death has rarely been studied in relation to the degree of the visibility of bodies, nor do many comparative analyses exist. This has led to a narrow understanding of how and why audiences are exposed to human suffering around the world. In examining newspaper images of the dead from the 2010 Haiti earthquake across 15 countries, this study develops a graphic image content scale to measure such visualizations. It finds significant differences in graphic images across the studied sample, both in terms of the amount of images and the degree of visibility of death. The study argues that major sociocultural influences, such as different religious traditions and societal levels of violence are part of the reason for the differences.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Deus vult: Images of crusader violence c. 1095-1100.

This study sets out to provide new information about the interaction between abstract religious ideas and actual acts of violence in the early crusading movement. The sources are asked, whether such a concept as religious violence can be sorted out as an independent or distinguishable source of aggression at the moment of actual bloodshed. The analysis concentrates on the practitioners of sacred violence, crusaders and their mental processing of the use of violence, the concept of the violent act, and the set of values and attitudes defining this concept. The scope of the study, the early crusade movement, covers the period from late 1080 s to the crusader conquest of Jerusalem in 15 July 1099. The research has been carried out by contextual reading of relevant sources. Eyewitness reports will be compared with texts that were produced by ecclesiastics in Europe. Critical reading of the texts reveals both connecting ideas and interesting differences between them. The sources share a positive attitude towards crusading, and have principally been written to propagate the crusade institution and find new recruits. The emphasis of the study is on the interpretation of images: the sources are not asked what really happened in chronological order, but what the crusader understanding of the reality was like. Fictional material can be even more crucial for the understanding of the crusading mentality. Crusader sources from around the turn of the twelfth century accept violent encounters with non-Christians on the grounds of external hostility directed towards the Christian community. The enemies of Christendom can be identified with either non-Christians living outside the Christian society (Muslims), non-Christians living within the Christian society (Jews) or Christian heretics. Western Christians are described as both victims and avengers of the surrounding forces of diabolical evil. Although the ideal of universal Christianity and gradual eradication of the non-Christian is present, the practical means of achieving a united Christendom are not discussed. The objective of crusader violence was thus entirely Christian: the punishment of the wicked and the restoration of Christian morals and the divine order. Meanwhile, the means used to achieve these objectives were not. Given the scarcity of written regulations concerning the use of force in bello, perceptions concerning the practical use of violence were drawn from a multitude of notions comprising an adaptable network of secular and ecclesiastical, pre-Christian and Christian traditions. Though essentially ideological and often religious in character, the early crusader concept of the practise of violence was not exclusively rooted in Christian thought. The main conclusion of the study is that there existed a definable crusader ideology of the use of force by 1100. The crusader image of violence involved several levels of thought. Predominantly, violence indicates a means of achieving higher spiritual rewards; eternal salvation and immortal glory.