Analysis of textural image features for content based retrieval

Digital archaelogy and virtual reality with archaeological artefacts have been quite hot research topics in the last years 55,56 . This thesis is a preperation study to build the background knowledge required for the research projects, which aim to computerize the reconstruction of the archaelogical data like pots, marbles or mosaic pieces by shape and ex ural features. Digitalization of the cultural heritage may shorten the reconstruction time which takes tens of years currently 61 ; it will improve the reconstruction robustness by incorporating with the literally available machine vision algorithms and experiences from remote experts working on a no-cost virtual object together. Digitalization can also ease the exhibition of the results for regular people, by multiuser media applications like internet based virtual museums or virtual tours. And finally, it will make possible to archive values with their original texture and shapes for long years far away from the physical risks that the artefacts currently face. On the literature 1,2,3,5,8,11,14,15,16 , texture analysis techniques have been throughly studied and implemented for the purpose of defect analysis purposes by image processing and machine vision scientists. In the last years, these algorithms have been started to be used for similarity analysis of content based image retrieval 1,4,10 . For retrieval systems, the concurrent problems seem to be building efficient and fast systems, therefore, robust image features haven't been focused enough yet. This document is the first performance review of the texture algorithms developed for retrieval and defect analysis together. The results and experiences gained during the thesis study will be used to support the studies aiming to solve the 2D puzzle problem using textural continuity methods on archaelogical artifects, Appendix A for more detail. The first chapter is devoted to learn how the medicine and psychology try to explain the solutions of similiarity and continuity analysis, which our biological model, the human vision, accomplishes daily. In the second chapter, content based image retrieval systems, their performance criterias, similiarity distance metrics and the systems available have been summarized. For the thesis work, a rich texture database has been built, including over 1000 images in total. For the ease of the users, a GUI and a platform that is used for content based retrieval has been designed; The first version of a content based search engine has been coded which takes the source of the internet pages, parses the metatags of images and downloads the files in a loop controlled by our texture algorithms. The preprocessing algorithms and the pattern analysis algorithms required for the robustness of the textural feature processing have been implemented. In the last section, the most important textural feature extraction methods have been studied in detail with the performance results of the codes written in Matlab and run on different databases developed

Fine Art Pattern Extraction and Recognition

This is a reprint of articles from the Special Issue published online in the open access journal Journal of Imaging (ISSN 2313-433X) (available at: https://www.mdpi.com/journal/jimaging/special issues/faper2020)

Spatial and Temporal Factors Affecting Human Visual Recognition Memory

The current thesis investigated the effects of a variety of spatial and temporal factors on visual recognition memory in human adults. Continuous recognition experiments investigated the effect of lag (the number of items intervening between study and test) on recognition of a variety of stimulus sets (common objects, face-like stimuli, fractals, trigrams), and determined that recognition of common objects was superior to that of other stimulus types. This advantage was largely eradicated when common objects of only one class (birds) were tested. Continuous recognition confounds the number of intervening items with the time elapsed between study and test presentations of stimuli. These factors were separated in an experiment comparing recognition performance at different rates of presentation. D-prime scores were affected solely by the number of intervening items, suggesting an interference-based explanation for the effect of lag. The role of interference was investigated further in a subsequent experiment examining the effect of interitem similarity on recognition. A higher level of global similarity amongst stimuli was associated with a lower sensitivity of recognition. Spatial separation between study and test was studied using same/different recognition of face-like stimuli, and spatial shifts between study and test locations. An initial study found a recognition advantage for stimuli that were studied and tested in the same peripheral location. However, the introduction of eye-tracking apparatus to verify fixation resulted in the eradication of this effect, suggesting that it was an artefact of uncontrolled fixation. Translation of both face-like and fractal stimuli between areas of different eccentricity, with different spatial acuities, did decrease recognition sensitivity, suggesting a partial positional specificity of visual memory. These phenomena were unaffected by 180 degree rotation. When interfering stimuli were introduced between study and test trials, translation invariance at a constant eccentricity broke down

Spatial and Temporal Factors Affecting Human Visual Recognition Memory

The current thesis investigated the effects of a variety of spatial and temporal factors on visual recognition memory in human adults. Continuous recognition experiments investigated the effect of lag (the number of items intervening between study and test) on recognition of a variety of stimulus sets (common objects, face-like stimuli, fractals, trigrams), and determined that recognition of common objects was superior to that of other stimulus types. This advantage was largely eradicated when common objects of only one class (birds) were tested. Continuous recognition confounds the number of intervening items with the time elapsed between study and test presentations of stimuli. These factors were separated in an experiment comparing recognition performance at different rates of presentation. D-prime scores were affected solely by the number of intervening items, suggesting an interference-based explanation for the effect of lag. The role of interference was investigated further in a subsequent experiment examining the effect of interitem similarity on recognition. A higher level of global similarity amongst stimuli was associated with a lower sensitivity of recognition. Spatial separation between study and test was studied using same/different recognition of face-like stimuli, and spatial shifts between study and test locations. An initial study found a recognition advantage for stimuli that were studied and tested in the same peripheral location. However, the introduction of eye-tracking apparatus to verify fixation resulted in the eradication of this effect, suggesting that it was an artefact of uncontrolled fixation. Translation of both face-like and fractal stimuli between areas of different eccentricity, with different spatial acuities, did decrease recognition sensitivity, suggesting a partial positional specificity of visual memory. These phenomena were unaffected by 180 degree rotation. When interfering stimuli were introduced between study and test trials, translation invariance at a constant eccentricity broke down

Framework for Automatic Identification of Paper Watermarks with Chain Codes

Title from PDF of title page viewed May 21, 2018Dissertation advisor: Reza DerakhshaniVitaIncludes bibliographical references (pages 220-235)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2017In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections.Introduction -- Paper and paper watermarks -- Automatic identification of paper watermarks -- Rotation, Scale and translation invariant chain code -- Comparison of RST_Invariant chain code -- Automatic identification of watermarks with chain codes -- Watermark composite feature vector -- Summary -- Appendix A. Watermarks from the Bernstein Collection used in this study -- Appendix B. The original and transformed images of watermarks -- Appendix C. The transformed and scaled images of watermarks -- Appendix D. Example of chain cod

Proceedings of KogWis 2012. 11th Biannual Conference of the German Cognitive Science Society

The German cognitive science conference is an interdisciplinary event where researchers from different disciplines -- mainly from artificial intelligence, cognitive psychology, linguistics, neuroscience, philosophy of mind, and anthropology -- and application areas -- such as eduction, clinical psychology, and human-machine interaction -- bring together different theoretical and methodological perspectives to study the mind. The 11th Biannual Conference of the German Cognitive Science Society took place from September 30 to October 3 2012 at Otto-Friedrich-Universität in Bamberg. The proceedings cover all contributions to this conference, that is, five invited talks, seven invited symposia and two symposia, a satellite symposium, a doctoral symposium, three tutorials, 46 abstracts of talks and 23 poster abstracts

Grounding the Linking Competence in Culture and Nature. How Action and Perception Shape the Syntax-Semantics Relationship

Part I of the book presents my basic assumptions about the syntax-semantics relationship as a competence of language users and compares them with those of the two paradigms that presently account for most theoretical linguistic projects, studies, and publications. I refer to them as Chomskyan Linguistics and Cognitive-Functional Linguistics. I will show that these approaches do not provide the means to accommodate the sociocultural origins of the “linking” competence, creating the need for an alternative approach. While considering these two approaches (sections 2.1 and 2.3), an alternative proposal will be sketched in section 2.2, using the notion of “research programme”. Thus, part I deals mainly with questions of the philosophy of science. Nevertheless, the model underlying the research programme gives structure to the procedure followed throughout the rest of the book, since it identifies the undertaking as multidisciplinary, following from the central roles of perception and action/attribution. This means that approaching the competence of relating form to content as characterized above requires looking into these sub-competences first, since the former draws upon the latter. Part I concludes with the formulation of an action-theoretic vocabulary and taxonomy (section 2.4). This vocabulary serves as the guideline for how to talk about the subject-matter of each of these disciplines. Part II and chapter 3 then deal with the sub-competences that have been identified as underlying linguistic competence. They concern the use of perception, identification/categorization, conceptualization, action, attribution, and the use of linguistic symbols. Section 3.1 in part II deals with perception. In particular, two crucial properties of perception will be discussed: that it consists of a bottom-up part and a top-down part, and that the output of perception is underspecified in the sense that what we perceive is not informative with respect to actional, i.e., socially relevant matters. The sections on perception to some degree anticipate the characterization of conceptualization in section 3.2 because the latter will be reconstructed as simulated perception. The property of underspecification is thus sustained in conceptualization, too. If utterances encode concepts and concepts are underspecified with respect to those matters that are most important for everyday interaction, one wonders how verbal interaction can (actually) be successful. Here is where action competence and attribution come into play (the non-conceptual contents referred to above). I will show that native speakers act and cognize according to particular socio-cognitive parameters, on the basis of which they make socially relevant attributions. These in turn specify what was underspecified about concepts beforehand. In other words, actional knowledge including attribution must complement concepts in order to count as the semantics underlying linguistic utterances. Sections 3.3 and 3.4 develop a descriptive means for semantic contents. I present the inherent structural organization of concepts and demonstrate how the spatial and temporal aspects of conceptualization can be systematically related to the syntactic structures underlying utterances. In particular, I will argue that conceptualization is organized by means of trajector-landmark configurations which can quite regularly be related to parts of speech in syntactic constructions using the notion of diagrammatic iconicity. Given a diagrammatic mapping and conceptualization as simulated perception the utterance thus becomes something like an instruction to simulate a perception. In part III, section 4.1 deals with the question of what the formal constituents of utterances/constructions contribute to the building of a concept from an utterance. In this context a theory of the German dative is presented, based on the theoretical notions developed throughout this work. Section 4.2 sketches the non-formal properties that reduce the remaining underspecification. In this context one of the most fundamental cognitive properties of language users is uncovered, namely their need to find the cause of any event they are cognizing about. I will then outline the consequences of this property for language production and comprehension. Section 4.3 lists the most important linking schemas for German on the basis of the most important constructions, i.e., motivated conceptualization-syntactic construction mappings, and then describes in a step-by-step manner how – from the utterance-as-instruction-for-conceptualization perspective – such an instruction is obeyed, and how such an instruction is built up from the perception of an event, respectively. The last section, 4.4, is dedicated to a discussion of some of the most famous and most puzzling linguistic phenomena which theoretical linguists traditionally deal with. In discussing the formal aspects of the linguistic competence, examples from German are used

Hierarchical learning : theory with applications in speech and vision

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 123-132).Over the past two decades several hierarchical learning models have been developed and applied to a diverse range of practical tasks with much success. Little is known, however, as to why such models work as well as they do. Indeed, most are difficult to analyze, and cannot be easily characterized using the established tools from statistical learning theory. In this thesis, we study hierarchical learning architectures from two complementary perspectives: one theoretical and the other empirical. The theoretical component of the thesis centers on a mathematical framework describing a general family of hierarchical learning architectures. The primary object of interest is a recursively defined feature map, and its associated kernel. The class of models we consider exploit the fact that data in a wide variety of problems satisfy a decomposability property. Paralleling the primate visual cortex, hierarchies are assembled from alternating filtering and pooling stages that build progressively invariant representations which are simultaneously selective for increasingly complex stimuli. A goal of central importance in the study of hierarchical architectures and the cortex alike, is that of understanding quantitatively the tradeoff between invariance and selectivity, and how invariance and selectivity contribute towards providing an improved representation useful for learning from data. A reasonable expectation is that an unsupervised hierarchical representation will positively impact the sample complexity of a corresponding supervised learning task.(cont.) We therefore analyze invariance and discrimination properties that emerge in particular instances of layered models described within our framework. A group-theoretic analysis leads to a concise set of conditions which must be met to establish invariance, as well as a constructive prescription for meeting those conditions. An information-theoretic analysis is then undertaken and seen as a means by which to characterize a model's discrimination properties. The empirical component of the thesis experimentally evaluates key assumptions built into the mathematical framework. In the case of images, we present simulations which support the hypothesis that layered architectures can reduce the sample complexity of a non-trivial learning problem. In the domain of speech, we describe a 3 localized analysis technique that leads to a noise-robust representation. The resulting biologically-motivated features are found to outperform traditional methods on a standard phonetic classification task in both clean and noisy conditions.by Jacob V. Bouvrie.Ph.D

Dual-Use Space Technology Transfer Conference and Exhibition

This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry