Image Fragments Research Articles

The technology of image matching by the criterion of conformity of image fragments samples

In this paper we considered the image matching problem. The problem is solved in the framework of an area approach based on the comparison of image fragments in the neighborhood of the points being compared. We proposed a new criterion of image fragments similarity based on the principle of image fragments samples conformity. An important advantage of the method is the possibility of comparison of very small image fragments. However, computation of this criterion is very time-consuming. So, we proposed parallel algorithm of conforming image matching using MPI. We evaluated acceleration and efficiency of parallel algorithm. The results of experiments on the “Cones” test images show high accuracy of the method.

A modified technique for smart textural feature selection to extract retinal regions of interest using image pre-processing

To increase the efficiency of the laser coagulation surgery the problem of the most accurate segmentation of fundus images is especially relevant. Fundus image segmentation is carried out with high accuracy using effective features and the minimum number of parameters for segmentation of a single image fragment. This paper describes a modified technique for smart textural feature selection to extract retinal regions of interest using image preprocessing algorithms. Preprocessing algorithms significantly influence the selected features which provide a minimum error of object recognition. In addition image preprocessing algorithms provide a more precise object selection. The informativeness of the obtained feature space is studied using discriminant data analysis. The best fragmentation block size segmentation and feature sets provides the necessary accuracy to identify regions of interest. Those regions are determined by the analysis of the following 4 classes of fundus images: exudates, thick, thin vessels and healthy areas. The advantages and disadvantages of the considered preprocessing algorithms were identified.

New scheme for fast copy-move detection

Image forgery detection is a challenging and important problem for many years. One of the most frequently used types of forgery (copy-move) is copying and pasting image fragment within the same image. There are exist two main types of copy-move forgeries: on the one hand, they are created without applying transformations (plain copy-move) and on the other – different digital transforms can be used to hide the traces of copy-move forgery (transformed copy-move). To solve the task of copy-move forgery detection in a complex way we propose several novel techniques, described further. The carried out research showed high quality of copy-move detection with intensity shift, contrast enhancement and additive noise distortions. In conclusion part we provide limitations of the scheme and the ranges of distortion parameters that can be detected.

Application of knowledge‐based cognitive CAPTCHA in Cloud of Things security

SummaryCurrent visual CAPTCHA designs are incorporating a number of techniques, which should prevent bots or unauthorized users from correct image fragmentation and symbol recognition, but the designs are varying very much in level of safety and robustness and may not be user‐friendly enough for broader use. This paper attempts to evaluate strengths and weaknesses of current solutions, from the security and user‐friendliness point of view. It also presents another approach to visual CAPTCHA generating algorithm that consists of many different styles of letters, combined with a purposeful background. Depicted CAPTCHA was created with the focus centered on strengthening scheme against different image detection techniques, especially character and pattern recognition. Such CAPTCHA can be applied for different security purposes in modern Cloud of Things technologies. In this paper is also presented an idea of cognitive CAPTCHAs which required special knowledge and perceptual skills. Such CAPTCHA may play important role in future security protocols.

Subpixel Estimation of the Node Coordinates of Quasiperiodic Textures

An algorithm is proposed to estimate the node coordinates of deformed lattices of quasiperiodic textures with subpixel accuracy. The algorithm consists of two steps. In the first step, the frequency and initial phase vectors of a polyharmonic brightness function model are calculated from the characteristics of spectral outliers of image fragments. The obtained estimates are used to determine the coordinates of the nodes of the local lattice. In the second step, the local lattices are combined into a global lattice for the entire image of the quasi-periodic texture. Using high-accuracy estimates of model parameters from small image fragments ensures stable operation of the algorithm for significant deformations of the lattice and sub-pixel accuracy in estimating the coordinates of its nodes. Results of computer simulation and processing of real halftone images of quasiperiodic textures are given demonstrating the effectiveness of the proposed algorithm.

Спосіб комплексування зображень різних діапазонів хвиль з метою створення універсальних еталонів для комбінованих кореляційно-екстремальних систем навігації

To ensure the accuracy of navigation and aiming of modern unmanned aerial vehicles and cont-rolled means of destruction in any weather conditions and time of day, in conditions of interference, the most promising is the joint use of sensors of various physical nature for the detection and identification of targets (objects to be defeated). In this case, combined correlation-extremal systems are used to solve the problems of navigation (guidance). For the operation of such systems, it is advisable to form universal reference images. The methods for integrating digital images of a different range of waves to create universal reference images used in combined correlation-extremal navigation systems are analyzed. To form a universal reference image it is necessary to solve the problem of obtaining a «combined» image on the basis of seve-ral initial images of the same section of the terrain in different wave ranges. In this case, the problem of integrating images for the subsequent synthesis of a universal reference image is conveniently reduced to the task of combining in one image the characteristics common to the optical and radar images — the original images. That is why there is proposed a method for integrating radar and grayscale optical images which allows to create digital grayscale image combining the main informative signs of images of both ranges. The use of this method leads to an increase of the brightness and contrast of common fragments of the original images, does not lead to the destruction of correlation links, therefore the resulting composite images can use to form universal reference images.

An efficient stereo matching based on fragment matching

We propose a stereo matching method based on image fragments. Unlike traditional pixel-based stereos matching methods, we use edge information in the reference image to divide it into small fragments, and we then use the segments to find the best matching fragments in another reference image from the horizontal and vertical directions. We obtain two disparity maps, and using the match confidence value for each disparity map, we can produce a more accurate disparity map. Next, we calculate the exact disparity value for each pixel within the fragment. Finally, the disparity map is filled and smoothed to obtain the final disparity result. Experiments demonstrated that the proposed method has low computation complexity, high matching accuracy, and the disparity of object edge is clear, and it achieved good performance with the Middlebury and KITTI benchmark.

Influence of Magnetically Conjugate Fragments of Auroral Emission Images on the Accuracy of Determining Eav of Precipitating Electrons

Results of magnetic conjugation of image fragments of auroral emissions at different altitudes along the magnetic field lines and preliminary results of evaluation of their influence on the accuracy of remote mapping of energy characteristics of precipitating electrons are presented. The results are obtained using the code of tracing being an integral part of the software Vector M intended for calculation of accompanying, geophysical, and astronomical information for the center of mass of a space vehicle (SV) and remote observation of aurora by means of Aurovisor-VIS/MP imager onboard the SV Meteor-MP to be launched.

Recognition-based character segmentation for multi-level writing style

Character segmentation is an important task in optical character recognition (OCR). The quality of any OCR system is highly dependent on character segmentation algorithm. Despite the availability of various character segmentation methods proposed to date, existing methods cannot satisfyingly segment characters belonging to some complex writing styles such as the Lanna Dhamma characters. In this paper, a new character segmentation method named graph partitioning-based character segmentation is proposed to address the problem. The proposed method can deal with multi-level writing style as well as touching and broken characters. It is considered as a generalization of existing approaches to multi-level writing style. The proposed method consists of three phases. In the first phase, a newly devised over-segmentation technique based on morphological skeleton is used to obtain redundant fragments of a word image. The fragments are then used to form a segmentation hypotheses graph. In the last phase, the hypotheses graph is partitioned into subgraphs each corresponding to a segmented character using the partitioning algorithm developed specifically for character segmentation purpose. Experimental results based on handwritten Lanna Dhamma characters datasets showed that the proposed method achieved high correct segmentation rate and outperformed existing methods for the Lanna Dhamma alphabet.

Digital watermarking method based on heteroassociative image compression and its realization with artificial neural networks

In this paper, we present a digital watermarking method and associated algorithms that use a heteroassociative compressive transformation to embed a digital watermark bit sequence into blocks (fragments) of container images. A principal feature of the proposed method is the use of the heteroassociative compressing transformation – a mutual mapping with the compression of two neighboring image regions of an arbitrary shape. We also present the results of our experiments, namely the dependencies of quality indicators of thus created digital watermarks, which show the container distortion level, and the probability of digital watermark extraction error. In the final section, we analyze the performance of the proposed digital watermarking algorithms under various distortions and transformations aimed at destroying the hidden data, and compare these algorithms with the existing ones.

COMPLEX TECHNOLOGY OF COMPUTER TESTING IN RUSSIAN AS A FOREIGN LANGUAGE

Problem and goal. At present, with the massive spread of computer technology and the growth of interest in the Russian language, by the citizens of foreign countries, is not developed and implemented in the Head and local testing centers in Russian as a foreign language (RCT) system of computer testing, not widely used modern methods and programs of statistical analysis of the results of computer testing and quality assessment of rehearsal and examination tests. Methodology. Two options developed by the authors of complex technologies «Tester» (the program “the Banker”, “Tester”, “Token”, “Statinfo”) and “Trester” (program “Protocol”, “Tsclient”, “Trester”, “Tranform”, “Thorny”) for computer-based testing by RCTS. Both variants have been tested in centralized testing and in Russian universities, are complex and versatile, providing the entire cycle of work - from the preparation of computer tests, computer testing, data collection, performance of operational statistical analysis of test results and statistical analysis of the quality of test items. Results. In technology «Trester» the possibility to completely switch to computer testing or part of a subtest to spend on computers and some on the forms. Rehearsal and examination testing for RCT can be carried out on computers for all sub-tests (vocabulary and grammar, reading, listening, writing, speaking). Automated expert work to check and evaluate on the computer the results of unformalized subtests (writing and speaking). In the article, as examples, show the fragments of images on the display screen when working with complex programs “Trester”. Conclusion. The urgency of creating a complex system of computer testing for RCT is substantiated. Two options of the initiative they have developed complex technologies “Tester” and “Trester” for computer testing in RCTS.

Antonio Ferro, o retrato e a entrevista: montagem e propaganda na encenação da História

The interviews of Antonio Ferro (1895-1956) to Salazar (1889-1970), gathered in the book Salazar, o Homem e a sua Obra [Salazar, the Man and his Work] (1933), inspired by the journalist Emil Ludwig's to Stalin (1878-1953) and Mussolini (1883-1945), are still today the best written portrait of the Head of Government of the Portuguese Dictatorship. This portrait appears as a cinematographic montage made of fragments of images woven with words. It is not a portrait as an exclusive domain of memory, but an image of spectacle that transfigures. This book also becomes the portrait of the future head of the Secretary of National Propaganda, Antonio Ferro. Either a portrait or portraits, these serialized interviews served as a powerful propaganda instrument during the staging of the nation's History and, simultaneously, became a testamentary remark. Additionally, it emphasizes the use of photographic images with propagandistic intention, not only as an illustration, but also as a testimony of the different moments during the interviews, as well as the importance of the photographic iconography of the 193o's.

Detecting image differences based on reference EMD-filters

In our previous works dealing with detecting differences in images in the case of substantial variations in brightness and geometry of an object, we proposed a morphological scheme for image analysis based on diffusion and reference mosaic filters. The filters were defined through the heat kernels of the similarity of image fragments. In this paper, we propose an implementation of this morphological scheme using original reference Earth mover's distance (EMD) filters, in which the optimal matrices of the mutual similarity of mosaic forms are calculated through a linear programming method.

Method of features construction for remote sensing images based on the characteristics of random point fields

Texture features are widely used in remote sensing image classification. In most cases they are extracted from grayscale images without taking color information into consideration. The texture descriptors, which consist of characteristics of random point fields formed for pixels of distinct intensity of grayscale and color band images are presented. The input image is divided into fragments for the elements of each of which the histogram is constructed and their local maxima are determined. Size of fragments are chosen depending on image resolution. For each of the intensity of the dynamic range of the image, a random point field, as a set of geometric centers of fragments, is formed. By the formed configuration, each field is classified as cluster, regular or random. To form a description of image elements a distribution of the number of field elements for each intensity and fragment is constructed. Separately, the vectors of the point field element for each intensity in the image fragment and the point field element for the selected intensity are formed. Experimental results demonstrate that proposed descriptors yield performance compared to other state-of-the-art texture features.

3Dlite

We present 3DLite 1 , a novel approach to reconstruct 3D environments using consumer RGB-D sensors, making a step towards directly utilizing captured 3D content in graphics applications, such as video games, VR, or AR. Rather than reconstructing an accurate one-to-one representation of the real world, our method computes a lightweight, low-polygonal geometric abstraction of the scanned geometry. We argue that for many graphics applications it is much more important to obtain high-quality surface textures rather than highly-detailed geometry. To this end, we compensate for motion blur, auto-exposure artifacts, and micro-misalignments in camera poses by warping and stitching image fragments from low-quality RGB input data to achieve high-resolution, sharp surface textures. In addition to the observed regions of a scene, we extrapolate the scene geometry, as well as the mapped surface textures, to obtain a complete 3D model of the environment. We show that a simple planar abstraction of the scene geometry is ideally suited for this completion task, enabling 3DLite to produce complete, lightweight, and visually compelling 3D scene models. We believe that these CAD-like reconstructions are an important step towards leveraging RGB-D scanning in actual content creation pipelines.

A New Intelligent Jigsaw Puzzle Algorithm Base on Mixed Similarity and Symbol Matrix

Jigsaw puzzle algorithm is important as it can be applied to many areas such as biology, image editing, archaeology and incomplete crime-scene reconstruction. But, still, some problems exist in the process of practical application, for example, when there are a large number of similar objects in the puzzle fragments, the error rate will reach 30%–50%. When some fragments are missing, most algorithms fail to restore the images accurately. When the number of fragments of the jigsaw puzzle is large, efficiency is reduced. During the intelligent puzzle, mainly the Sum of Squared Distance Scoring (SSD), Mahalanobis Gradient Compatibility (MGC) and other metrics are used to calculate the similarity between the fragments. On the basis of these two measures, we put forward some new methods: 1. MGC is one of the most effective measures, but using MGC to reassemble the puzzle can cause an error image every 30 or 50 times, so we combine the Jaccard and MGC metric measure to compute the similarity between the image fragments, and reassemble the puzzle with a greedy algorithm. This algorithm not only reduces the error rate, but can also maintain a high accuracy in the case of a large number of fragments of similar objects. 2. For the lack of fragmentation and low efficiency, this paper uses a new method of SSD measurement and mark matrix, it is general in the sense that it can handle puzzles of unknown size, with fragments of unknown orientation, and even puzzles with missing fragments. The algorithm does not require any preset conditions and is more practical in real life. Finally, experiments show that the algorithm proposed in this paper improves not only the accuracy but also the efficiency of the operation.

Answering why-not questions on semantic multimedia queries

Linked data is a promising way to publish media data as resources on the Web and interlink them with other resources. While significant amounts of image, audio and video fragments have been tagged ...

Calibration of Measuring Systems for the Expert Evaluation of Color Characteristics

Results of the development of the portable mobile color analyzer for sample surfaces using a digital camera are presented. The special program computes and analyzes the color characteristics of samples. The dominant wavelength and the saturation for each pixel as well as for the selected fragment of the digital image are calculated using the spectrum locus. To get the perfect linear color reproduction, the correction factors are introduced. Using the reference color atlas we define factors and carry out the calibration of analyzer′s measuring system by them. The special corrective procedure for the algorithm of the dominant wavelength calculation which enhances the accuracy for spectral colors up to ± 2.5 nm is elaborated. We tested the analyzer in experiments with meat samples produced at the poultry plants. The dominant wavelength could be used for recognizing meat quality characteristics. Experimental results demonstrated the significant differences in data for meat samples of different plants, and they indicated the real storage time of meat.

An oscillatory network model with controllable synchronization and a neuromorphic dynamical method of information processing

A spatially two-dimensional oscillatory neural network model with inhomogeneous modifiable oscillatory coupling is designed and an adaptive dynamical method of brightness image segmentation (image reconstruction) based on self-organized cluster synchronization in the oscillatory network is developed. The method imitates the known phenomenon of dynamical binding via synchronization that is presumably used by a number of the brain neural structures in their work. The oscillatory-network approach demonstrates the following capabilities: (1) high-quality segmentation of real grey-level and color images; (2) selective image segmentation (exclusion of unnecessary information); (3) solution of the simplest problem of object selection in a visual scene—the problem of the successive selection of all spatially separated image fragments of almost equal brightness.

The structure of Associative Fields of Stimuli природа / природа / прырода / die Natur in East Slavic and German Languages

The problem of the relationship between man and nature, society and nature is of current interest for many sciences. Global processes occurring in the world, also due to human activities, increasingly attract attention of community to the ecology, highlight the fragility of life in general and humans in particular. Thus, the topicality of research is determined by the need to solve the problem of harmonious coexistence of man and nature on the one hand, and the necessity to clarify the awareness of the mentioned issue by each community of people on the other. Psycholinguistic methods of research would help in a study of peculiarities of fragments of world image that hide behind the word "nature" in the linguistic consciousness of different ethnic groups. The objective of the research is the contrastive psycholinguistic analysis of associative fields of words-stimuli природа / природа / прырода / die Natur in order to reveal the general and specific features in images of linguistic consciousness of Ukrainians, Russians, Belarussians and Germans. Attitude to nature was formed by every nation in its own national cultural space, in a historical context, it reflects its value priorities. The material was obtained as a result of series of associative experiments in the early twenty-first century. The respondents were students of higher educational institutions of Ukraine, Russia, Belarus, Germany: 100 representatives from each nation. The material of the free associative experiment is used in this study. Associative fields of word-stimulus природа and its correlates in Russian, Belarusian and German languages were obtained in the result of processing experimental material. Comprehensive contrastive analysis of associative fields was conducted by the method of associative gestalt, that we understand as a solid image, which has a clear structure within the association field. As a result of research we have detected the similarities in the images of linguistic consciousness of Ukrainians, Russians, Belarusians, and Germans that can be explained mainly due to universal human values and differences. The gestalt structure of associative fields in each language clearly demostrate the differences in images of linguistic consciousness. The differences are seen in the different number of zones in four gestalts of studied languages, in the presence of some zones only in certain gestalt unlike others, in size of zones, that define their rating and originality of structure of each associative field, in quantitative and qualitative composition of zones as well as in the cores of gestalts.
 References
 
 Markovina, I., Danilova, Ye. (2000).Spetsifika jazikovogo soznaniya russkikh i amerikantsev: opit postroyeniya assotsiativnogo geshtalta” tekstovoriginala i perevoda. [Specificity ofthe linguistic consciousness of Russians and Americans: the experience of constructing ofthe “associative gestalt” of texts of original and translation]. In:Yazikovoye Soznaniye i Obraz Mira (pp. 116–132), N. V. Ufimtseva, (ed). Moscow:Institute of Linguistics of the Russian Academy of Sciences.