Image Fragments Research Articles

THE EVOLVEMENT OF BRAND IDENTITY OF LANGKAWI ISLAND, MALAYSIA

The purpose of this paper is to investigate the brand identity development efforts of Langkawi Island as one of the most prominent and well-guarded tourism destinations in Malaysia. It will be viewed from the historical perspectives for the last 35 years since the 1980s until the present time as to how this involvement influences the formation of its brand identity and later, the existing destination image. Based on in-depth interviews with eleven different levels of managers of separate divisions for destination management organizations (DMOs) in Langkawi Island, Malaysia, theoretically, the findings provide an opportunity to expand the knowledge of destination brand identity development and the involvement of DMOs in influencing image making over time. Practically, the findings indicate three key important antecedents of brand identity development efforts related to: (1) the effects from multiple positioning themes and slogans, (2) the important of brand coordination, and (3) brand leadership issue. These empirical findings provide new insights into enhancing the theoretical aspect of managing a destination brand, including its close relationship with issues faced by destination marketing organizations in managing destination branding strategy. Thus, using the case study of Langkawi Island, the context of multiple identities or image fragmentation is important to be understood due to the different perceived ideas on how the image should be projected according to stakeholders and market segmentation.

GROUPING METHOD OF IMAGE FRAGMENTS OF ADJACENT DISLOCATION ETCH PITS OF THE SEMICONDUCTOR WAFER

An increase in production volumes of gallium arsenide semiconductor devices determines the need for better control of dislocations of semiconductor wafer. The grouping method of image fragments of adjacent dislocation etch pits of the semiconductor wafer is proposed in the article. Adjacent fragments will be allocated in the pre-binarized image of wafer surface, which contains adjacent fragments of etch pits of dislocation loops after treatment by the described method. Improved methods for determining the loop line width determines the edge line width of etch pits of suspected dislocations, given the variability of their display in the binarized image. The current loop line width is compared to the reference line width of the dislocation loop. The grouping method of image fragments of adjacent dislocation etch pits of the semiconductor wafer defines recovery of loop lines branching, takes into account various options of line adjacency and determines the direction of further recovery of loop line of dislocation etch pits. A step by step description of the method is given.

Method of orthotransformation of space images in conditions of lack of cue

The paper introduces a method of prompt orthotransformation of space images, based on the integration of the orbital and polynomial methods of photogrammetric image processing. The concept of the method consists in fragmentary formation of an orthoimage. Fragments (quadrangles) of a definite size are marked in space images, so that geometric constraints between their elements are adequately described by a bidimensional polynom of the first order. The adjacent fragments have common vertexes on the contact line, providing integrity of the orthoimage being formed. The location of the fragment (the coordinates of its vertexes) is defined by the orbital method with consideration for the configuration of terrain, thus, if the fragment is small enough, it provides terrain correction for all the points of the fragment. To use the orbital method we define initial values of the orientation angles of the on-board equipment of the spaceship and the laws of variations of these angles in course of survey with subsequent specification of these values in terms of the coordinates of four check points. The compliance between tolerance points of fragments of the initial image and the image being formed is achieved on the basis of the models, the implementation of which is computationally less complex than that based on orbital methods. Experimental approbation of the proposed method proved that the method of prompt orthotransformation makes possible four-fold reduction of the time of photogrammetric space image processing while providing comparable accuracies of the resulting images.

Prototype system for feature extraction, classification and study of medical images

Colonoscopy exam images are useful to identify diseases, such as the colorectal cancer, which is one of the most common cancers worldwide. Computational image analysis and machine learning techniques can assist experts to identify abnormalities in these images. In this work, we present and evaluate MIAS 3.0, which aims to help experts to study and analyze colon tissue images. To do so, the system initially extracts features from these images. Currently, Amadasum, Haralick and Laws texture descriptors are supported. Then, the described images are classified into normal or abnormal images. In this version, J48, nearest neighbor, backpropagation based on multilayer perceptron, naive Bayes, and support vector machine classification algorithms are implemented. MIAS was developed with open source technologies using a software engineering approach to improve flexibility and maintainability. In this work, MIAS was quantitatively assessed by its application in a set of 134 tissue image fragments. The classifiers built from this set were compared according to the cross-validation and contingency table strategies. Also, the system was qualitatively evaluated using 12 heuristics by twelve volunteers from Health and Exact Sciences. The issues found were categorized according to Rolf Molich’s severity scale. As a result, the J48 classifier achieved the highest sensitivity (85.07%) and reasonable average error (18.68%). In the qualitative evaluation, 61.26% of the issues found were not considered serious. These assessments suggest that MIAS can be useful to assist domain experts with minimum knowledge in informatics to conduct more complete studies of medical images, by identifying patterns regarding different abnormalities.

AMSR-E sea surface temperature (SST) charts enhancement

Microwave satellite images used for retrieving sea surface temperatures often have such distortions as noise and blurring of the thermal fronts. An image processing approach based on the Mumford-Shah model of optimal image approximation is considered for the solution to this problem. We divide images into flat areas and frontal zones, and then process these areas separately. Image fragmentation is based on automatic detection of the thermal front lines. SST enhancement in frontal zones is achieved by using image deconvolution methods. It has been shown that SST errors in high gradient areas reach 1–3 °C. The proposed approach can decrease this discrepancy.

Dust Image Fragments Ghosts

Abstract ‘Dust Image Fragments Ghosts’ is an artistic exploration of my view of heterotopia from a writer’s perspective, the dimension of the fragmental, and the space in between the text and the reader. The starting point are 3D micrographs of dust samples from mobile and immobile cultural artefacts, which were part of a research project which investigated the aesthetic potential of dust and its information content from the perspective of the conservation and restoration. Dust has the power to make visible the absent, to show what must have been there. Fragments as a literary form show what might be there, in between or around. ‘Dust Image Fragments Ghosts’ follows the traces of seemingly empty space. It is a reflexive literary expedition into the landscapes of dust, a ghostly universe between micro and macro, reader and writer, image and imagination.

Experimental Research of High-Energy Capabilities of Material Recognition by Dual-Energy Method for the Low- Dose Radiation

The algorithm to produce primary radiographs, its transformation by dual energy method and recognition of the object materials were enhanced based on the analysis of experimental results. The experiments were carried out at the inspection complex with high X- ray source - betatron MIB 4/9 in Tomsk Polytechnic University. For the reduced X -ray dose rate, the possibility of recognition of the object materials with thickness from 20 to 120 g/cm2 was proved under the condition that as the dose rate is reduced by the defined number of times, the segment of the image fragment with the reliably identified material will increase by the same number of times.

Noise effect on the recognition of fragmented contour images

We compared the results of recognition of fragmented contour images in the presence of noise and without noise. Both the contour images and the visual noise were synthesized with Gabor elements. The spacing between fragments in contour images and between noise elements, as well as the sizes of images, varied irrespective of one another. The percentage of recognition did not depend on the size of stimuli, but it differed for various objects in the presence and absence of noise. The percentage of recognition was higher for images with lots of turns in the absence of noise and, on the contrary, for images with lengthy contours with a lightly varying curvature in the presence of noise. The thresholds of recognition in noise depended, in general, on the ratio of the spacing between the elements in noise to the spacing between contour fragments.

Stimulus features coded by single neurons of a macaque body category selective patch

Body category-selective regions of the primate temporal cortex respond to images of bodies, but it is unclear which fragments of such images drive single neurons' responses in these regions. Here we applied the Bubbles technique to the responses of single macaque middle superior temporal sulcus (midSTS) body patch neurons to reveal the image fragments the neurons respond to. We found that local image fragments such as extremities (limbs), curved boundaries, and parts of the torso drove the large majority of neurons. Bubbles revealed the whole body in only a few neurons. Neurons coded the features in a manner that was tolerant to translation and scale changes. Most image fragments were excitatory but for a few neurons both inhibitory and excitatory fragments (opponent coding) were present in the same image. The fragments we reveal here in the body patch with Bubbles differ from those suggested in previous studies of face-selective neurons in face patches. Together, our data indicate that the majority of body patch neurons respond to local image fragments that occur frequently, but not exclusively, in bodies, with a coding that is tolerant to translation and scale. Overall, the data suggest that the body category selectivity of the midSTS body patch depends more on the feature statistics of bodies (e.g., extensions occur more frequently in bodies) than on semantics (bodies as an abstract category).

Constellational contour parsing for deformable object detection

In this paper we propose a novel framework for contour-based object detection from cluttered environments. Given a contour model for a class of object, it is first decomposed into fragments, then in the test image we simultaneously perform selection of relevant contour fragments in edge images, grouping of the selected contour fragments, and finding best geometry-preserving matching to model contours. Finding the best matching is inherently a computationally expensive problem. To address this challenge, we developed local shape descriptors and an additive similarity metric function which can be computed locally while preserving the capability of matching deformable shapes globally. This allows us to establish a constellational shape parsing framework using low-complexity dynamic programming to find optimal configuration of contour segments in test images to match the model contour. To effectively detect objects with large deformation, we augmented the metric function with a local motion search, modeled the relationship between different shape parts using multiple concurrent dynamic programming shape parsers. Our experimental results show that the proposed method outperforms the state-of-the-art contour-based object detection algorithms on two benchmark datasets in terms of average precision.

English

English

The role of information sources in image fragmentation

•Relationship between perceived tourist image and information sources is analysed.•It was aimed to detect image fragmentation in the projected image.•593 questionnaires were used to measure perceived image through photo elicitation.•Emitted image fragmentation has effects on tourist perceived image of a destination.•Number and type of information sources influence tourist’s destination knowledge.

A Raindrop Unfallen: innocence and Jacques-Henri Bernardin de Saint Pierre's Paul and Virginia (1788)

The following essay is a creative, and challenging, reflection upon key themes of this special issue. The essay brings Jacques-Henri Bernardin de Saint Pierre's tragic romance, Paul and Virginia (1788), into conversation with an artistic response, Julia Margaret Cameron's 1865 photograph. Paul and Virginia is the tale of two children on the idyllic Ile de France, whose love encodes an eroticised innocence. Cameron's rendition offers a visual re-imagining of the fairy tale. In her appreciation of text and image, Carol Mavor negotiates a space between critical and poetic writing. Mosaic-like in form, evocative fragments of prose, poetry and images, are brought together to reflect upon the elusive nature of seduction, desire and innocence—especially among women, mothers and children. This experimental work uses artistic expression to enable us to think differently about the Victorians' troubling legacy of eroticised innocence, and explores new ways to describe inner experience.

THE METHODOLOGICAL ASPECTS OF IMAGE FRAGMENTATION AS THE PROBLEM OF COMPOSITION ORGANIZATION AS PART OF COMPOSITIONAL THEORY TEACHING

The article contains the basic definitions of the image fragmentation theory as part of teaching the “Basics of compositional theory” course to the Second Year students (four-year program) of the Arts Department. Some aspects of objects‟ perception, word picture‟s and compositional aim‟s formation may be found there as well. The article also attracts the reader‟s attention to the problem of the mutual contextual relationship between details and the unity. It also has a number of theoretical and practical problems and artistic tasks which can be solved by the use of compositional method of image fragmentation as part of the fragmentation theory basics‟ practical mastering. The article also includes some of the common characteristics of image fragmentation as a way of composition‟s formation on the basis of baroque graphic tradition. The article offers the methodological working practices for the composition of significance which is based on the image fragmentation basis. The methods are based on efficient verbs, the sum of logical, emotional, figurative transformations of the context and subtext of a layout, it determines how the fragment affects the one who sees it. The author has created the system for fragment‟s composition while teaching the Second Year students of the Arts Department. The process of creating the composition is regarded within the dialectic interconnections between the fragment‟s composition and composition of significance. The article also contains the practical tasks which could be fulfilled by students while designing the fragment‟s composition.

Efficient Rotation-Scaling-Translation Parameter Estimation Based on the Fractal Image Model

This paper deals with area-based subpixel image registration under the rotation-isometric scaling-translation transformation hypothesis. Our approach is based on parametrical modeling of geometrically transformed textural image fragments and maximum-likelihood estimation of the transformation vector between them. Due to the parametrical approach based on the fractional Brownian motion modeling of the local fragments' texture, the proposed estimator ML <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fBm</sub> (ML stands for “maximum likelihood” and fBm stands for “fractal Brownian motion”) has the ability to better adapt to real image texture content compared with other methods relying on universal similarity measures such as mutual information or normalized correlation. The main benefits are observed when assumptions underlying the fBm model are fully satisfied, e.g., for isotropic normally distributed textures with stationary increments. Experiments on both simulated and real images and for high and weak correlations between registered images show that the ML <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fBm</sub> estimator offers significant improvement compared with other state-of-the-art methods. It reduces translation vector, rotation angle, and scaling factor estimation errors by a factor of about 1.75-2, and it decreases the probability of false match by up to five times. In addition, an accurate confidence interval for ML <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fBm</sub> estimates can be obtained from the Cramér-Rao lower bound on rotation-scaling-translation parameter estimation error. This bound depends on texture roughness, noise level in reference and template images, correlation between these images, and geometrical transformation parameters.

The Fusion of the Visual and Thermal Images on the Basis of Determining the Image Fragments which Contain Essential Details

The aim of the following study was to develop a procedure which guarantees the data fusion of thermal and visual images. The first stage of the proposed algorithm consisted of images acquisition which guaranteed that the same parts of images represented the same parts of the observed terrain. The second stage depended on previous information about the searched object features. Two different situations were considered herein. In the case when we had the searched object’s feature vector for both representations of a searched object, we could conduct the pattern recognition for each image. It was conducted separately for visual and thermal images. In this way, we obtained the important parts of the images which should be represented in a fused image. The other case examined in the paper, considered the situation in which we did not have the formalised information about the object. In this case, it was necessary to analyse whole images in order to define the potential parts of the images where the object could be found. This analysis should be helpful for an operator to indicate the parts of the images where there are some artefacts which can be the elements of the searched object. Therefore, in this case, the second stage of the algorithm consisted in calculating the local features of the images. These features constituted grey scale gradient computed for the pixels inside the aperture. This study presented the examples of the fused images obtained by means of the developed method.

A copy-move detection algorithm based on binary gradient contours

Copy-move is one of the most obvious ways of deliberate distortion of digital images in order to conceal the information contained in them. The process of duplicate embedding consists in copying an image fragment and pasting it within the same image. Prior to pasting, the fragment can be distorted using transformations such as contrast enhancement, noise adding, scaling, rotation, and combinations thereof. Existing approaches to copy-move forgery detection are based on calculating feature vectors for overlapping blocks of an image and then using these vectors to find the closest regions in Euclidean space. In this paper, we propose features based on binary gradient contours, which are resistant to contrast enhancement, additive noise and JPEG compression. We also present results of conducted experiments for demonstrating the proposed algorithm effectiveness for a range of distortion parameters. The research also involves comparing features based on binary gradient contours with features based on various forms of local binary patterns.

Functional Organization of the Brain during Preparation for Recognition of Image Fragments

Studies in adult subjects (n = 36) analyzed functional interactions in the prefrontal areas of the cortex with other cortical zones during preparation to recognize incomplete figures with different levels of fragmentation during sequential approximation to the complete image. Functional interactions were measured in terms of the imaginary part of the complex coherence of the EEG α rhythm. The nature of rearrangements in intracortical interactions was found to differ in subjects with high and low levels of recognition success. In successful subjects, changes in intracortical interactions during the period preceding as yet unrecognized stimuli occurred mainly in the right hemisphere, while during the period preceding recognized stimuli changes were mainly in the left hemisphere. In this group of subjects, α-rhythm coherence in both hemispheres increased in the situation of focused attention as compared with the situation of nonspecific attention. In unsuccessful subjects, conversely, α-rhythm coherence levels in both the right and left hemispheres decreased significantly on focused attention as compared with nonspecific attention. These results provide evidence that the co-tuning of electrical activity in the cortical zones, in terms of the α rhythm, is one of the mechanisms of their functional unification during the period of preparation to recognize incomplete figures.

Scene coherence can affect the local response to natural images in human V1.

Neurons in primary visual cortex (V1) can be indirectly affected by visual stimulation positioned outside their receptive fields. Although this contextual modulation has been intensely studied, we have little notion of how it manifests with naturalistic stimulation. Here, we investigated how the V1 response to a natural image fragment is affected by spatial context that is consistent or inconsistent with the scene from which it was extracted. Using functional magnetic resonance imaging at 7 T, we measured the blood oxygen level-dependent signal in human V1 (n = 8) while participants viewed an array of apertures. Most apertures showed fragments from a single scene, yielding a dominant perceptual interpretation which participants were asked to categorize, and the remaining apertures each showed fragments drawn from a set of 20 scenes. We find that the V1 response was significantly increased for apertures showing image structure that was coherent with the dominant scene relative to the response to the same image structure when it was non-coherent. Additional analyses suggest that this effect was mostly evident for apertures in the periphery of the visual field, that it peaked towards the centre of the aperture, and that it peaked in the middle to superficial regions of the cortical grey matter. These findings suggest that knowledge of typical spatial relationships is embedded in the circuitry of contextual modulation. Such mechanisms, possibly augmented by contributions from attentional factors, serve to increase the local V1 activity under conditions of contextual consistency.

Feature description of informative fragments in the problem of computerized attribution of paintings

Problems of composing a feature description and developing a comparison procedure for the images of paintings in attribution are considered. A feature description of a facture of paintings based on the characteristics of a grayscale image relief and elements of the structure tensor is proposed. In contrast to known techniques, the feature description is formed only by informative fragments of images and does not require preliminary segmentation of individual brushstrokes. Parameters of feature extraction procedures are chosen. Measures of dissimilarity between images of paintings are proposed. Computational experiments are carried out. The feature description proposed is a quantitative characteristic of the artistic style of an author. The procedure developed for comparing images can be applied together with other types of investigation of paintings to make an attributional conclusion.