{"title":"Pyramid of Filters - Fast Image Filtering without FFT","authors":"S. Ershov, I. Valiev, A. Voloboy","doi":"10.51130/graphicon-2020-2-3-4","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-4","url":null,"abstract":"Methods of computer graphics which had already become common in design of new optical systems and materials find currently new applications such as stomatology and ophthalmology. Some modern imaging systems are now designed in conjunction with the human vision system which is at their end. Asa result simulation of the effects of human vision becomes necessary. These include partial defocusing and resulting \"blur\" of image, scattering and halo/corona and so on. Such effects are usually simulated convolving the original, \"ideal\" image with the pixel spread function. The latter frequently has size about that of the source image, so straightforward calculation of convolution would take a giant number of operations. Therefore in case of high resolution a decent speedis usually achieved by using the Fast Fourier Transform (FFT) for convolution,but since FFT operates periodic functions on a lattice with resolution being an integer power of a prime numbers, the required working resolution may considerably increase that of the original image and required memory becomes inadmissible. This paper presents an alternative method that allows calculations in much smaller memory avoiding overheads introduced by FFT requirements.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116580985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of PTC «Graphics –TR» for Teaching University Students on the Course Computer Simulation of Circuits and Devices»","authors":"S. Smirnov, L. Sizova","doi":"10.51130/graphicon-2020-2-3-58","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-58","url":null,"abstract":"This paper describes the capabilities of the Graphics-TR programmatically technical complex (PTC) as a tool for teaching university students the general principles of computer-aided design of schematic documentation using the Graphics-TP programmatically technical complex. A brief history of the development of CAD, CAM and PDM systems in our country and abroad is presented. The main disadvantages of using foreign CAD in Russia are given. Attention is focused on electronic design automation (EDA) systems for circuit engineering tasks, which is a subspecies of CAD systems. The article provides a justification for the development of domestic software at the scientific Institute (Computer Graphics Laboratory, part of the division of the V. A. Trapeznikov Institute of management problems of the Russian Academy of Sciences) for solving problems in the field of EDA design. With the help of \"Graphics –TR\", we consider computer modeling of circuits by automating design work on the example of a practical solution to the problem in the field of circuit engineering and development of printed circuit boards. There are also examples of practical classes on the study of circuitry by students of MTUCI on the course of lectures \"Computer modeling of circuits and devices\".","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"323 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wavefront Parameters Recovering by Using Point Spread Function","authors":"O. Kalinkina, T. Ivanova, Ju.O. Kushtyseva","doi":"10.51130/graphicon-2020-2-4-47","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-4-47","url":null,"abstract":"At various stages of the life cycle of optical systems, one of the most important tasks is quality of optical system elements assembly and alignment control. The different wavefront reconstruction algorithms have already proven themselves to be excellent assistants in this. Every year increasing technical capacities opens access to the new algorithms and the possibilities of their application. The paper considers an iterative algorithm for recovering the wavefront parameters. The parameters of the wavefront are the Zernike polynomials coefficients. The method involves using a previously known point spread function to recover Zernike polynomials coefficients. This work is devoted to the research of the defocusing influence on the convergence of the algorithm. The method is designed to control the manufacturing quality of optical systems by point image. A substantial part of the optical systems can use this method without additional equipment. It can help automate the controlled optical system adjustment process.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129543724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of Vector Transformations for Russian Word2Vec and FastText Embeddings","authors":"Olga Korogodina, Olesya Karpik, E. Klyshinsky","doi":"10.51130/graphicon-2020-2-3-18","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-18","url":null,"abstract":"Authors of Word2Vec claimed that their technology could solve the word analogy problem using the vector transformation in the introduced vector space. However, the practice demonstrates that it is not always true. In this paper, we investigate several Word2Vec and FastText model trained for the Russian language and find out reasons of such inconsistency. We found out that different types of words are demonstrating different behavior in the semantic space. FastText vectors are tending to find phonological analogies, while Word2Vec vectors are better in finding relations in geographical proper names. However, we found out that just four out of fifteen selected domains are demonstrating accuracy more that 0.8. We also draw a conclusion that in a common case, the task of word analogies could not be solved using a random word pair taken from two investigated categories. Our experiments have demonstrated that in some cases the length of the vectors could differ more than twice. Calculation of an average vector leads to a better solution here since it closer to more vectors.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132356119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandr A. Kuzmenko, S. Kondratenko, K. Dergachev, Valery Spasennikov
{"title":"Ergonomic Support for Logo Development Based on Deep Learning","authors":"Alexandr A. Kuzmenko, S. Kondratenko, K. Dergachev, Valery Spasennikov","doi":"10.51130/graphicon-2020-2-4-42","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-4-42","url":null,"abstract":"Every year rendering logos becomes an increasingly important task in various fields. One of the most interesting methods for rendering logos is the use of neural networks. This paper proposes a method for rendering logos using a convolutional neural network (CNN), specially trained to classify objects based on a single keyword and to select parametric characteristics of the logo. Special attention is paid to the ergonomic evaluation of resulting logos and the feasibility of the proposed method is experimentally confirmed. The research has shown that the results obtained are superior compared to the most modern approaches.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114225825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Sokolov, D. Zhdanov, I. Potemin, A. Zhdanov, N. Deryabin
{"title":"A Bidirectional Scattering Function Reconstruction Method Based on Optimization of Microrelief Heights Distribution","authors":"V. Sokolov, D. Zhdanov, I. Potemin, A. Zhdanov, N. Deryabin","doi":"10.51130/graphicon-2020-2-3-6","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-6","url":null,"abstract":"The work is devoted to the development of a new method for reconstructing the scattering properties of a rough surface, which is described using the bi-directional scattering distribution function (BSDF). There are several different methods of BSDF reconstruction using various approaches. However, they all have their drawbacks: for example, a method based on modeling the measured distribution of heights often requires a complicated fit apart from the expensive measurements themselves, various analytical methods are usu-ally operable within the average roughness values with their standard distribution, and a rather good and universal method for optimizing the normals distribution density does not support internal reflections on the elements of the roughest surface. The proposed solution uses the geometry models of the rough surface, which allows simulating a physically more accurate propagation of light through the rough surface taking into account internal reflections, and hence a more accurate reconstruction of the bidirectional scattering distribution function. The results of BSDF reconstruction with the new method are proved by comparison with measurement results.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115134437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Visualizing Global Socio-Technogenic Human Transformation: Digital Challenges of Living Earth","authors":"E. Dergacheva, E. Demidenko","doi":"10.51130/graphicon-2020-2-3-44","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-44","url":null,"abstract":"In the XXI century, the world of man and nature develops mainly in socio-technogenic living conditions. Global technospherization of the planet Earth is the most important cause of continuous socio-cultural, techno-medical and biological changes in man. In technical, natural and human studies a human is usually considered from the point of view of only one discipline. This narrow approach leaves its incorrect mark when recreating the new image of a human in the virtual environment of the digital image of the world. Digital Earth technologies establish a link between the spheres: social, biospheric, natural-inanimate and artificial, created by society using a number of important sciences. It is necessary to approach systematically the representation of the evolving human being in the constantly updated digital space of the planet, to supplement the existing developments of scientists with a scientific and philosophical understanding of the interdisciplinary processes of socio-technogenic development of the biosphere life. Scientific visualization of interrelated evolutionary changes in man is of great interest for the Digital Earth project both from the point of view of studying anthropogenesis, and from the point of view of developing promising programs for preserving his biosphere body and natural health in a developing socio-technogenic world.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Neural Network Classifier of Oil Pollution on the Water Surface when Processing Radar Images","authors":"T. Tatarnikova, E. Chernetsova","doi":"10.51130/graphicon-2020-2-3-42","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-42","url":null,"abstract":"The paper proposes a solution to the problem of detecting oil pollution on a monochrome radar image. The detection of oil pollution in the image includes the solution of three tasks: detecting a dark object on the image, highlighting the main characteristics of a dark object, classifying a dark object as oil pollution or natural slick. Various characteristics of a dark object are proposed based on the contrast between the object and the background. It is proposed to use a neural network as a classifier. The input parameters of the neural network classifier of the dark image object are proposed. A technique for determining the structure of a neural classifier is presented. An algorithm for testing the selected structure of the neural network for the suitability of classifying the dark area on the image of the water surface as oil pollution or wind slick is proposed. The results of the work of the neural network classifier program for detecting abnormal objects in radar images are demonstrated.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134037123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Andreev, A. Bondarev, A. Bondarenko, V. Galaktionov, N. Bondareva
{"title":"Constructing Stereo Images of Error Surfaces in Problems of Numerical Methods Verification","authors":"S. Andreev, A. Bondarev, A. Bondarenko, V. Galaktionov, N. Bondareva","doi":"10.51130/graphicon-2020-2-3-21","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-21","url":null,"abstract":"The tasks of constructing stereo representations of texts and formulas on an autostereoscopic monitor in stereo presentations designed to display the results of numerical modeling are an urgent sub-task in developing methods and algorithms for constructing stereo displays of scientific research results. In this paper, the construction of stereo images on an autostereoscopic monitor is considered. The autostereoscopic monitor allows you to watch stereo images without glasses, while ensuring the quality of the stereo image, which is not inferior to the quality of the stereo image presented using the classic 3D projection stereo system. The possibility of combining several stereo objects with different parameters on one frame with various parameters allowing to achieve the maximum stereo effect is being investigated. This technology has been applied practically to visualize the problems of verification of numerical methods and their comparative analysis. Similar solutions for the two-parameter problem are represented in the form of error surfaces constructed for each numerical method involved in the comparison. The construction of error surfaces in stereo mode is implemented for an autostereoscopic monitor based on a multi-view.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Alekseev, A. Bondarev, V. Galaktionov, A. Kuvshinnikov, L. Shapiro
{"title":"On Applying of Generalized Computational Experiment to Numerical Methods Verification","authors":"A. Alekseev, A. Bondarev, V. Galaktionov, A. Kuvshinnikov, L. Shapiro","doi":"10.51130/graphicon-2020-2-3-19","DOIUrl":"https://doi.org/10.51130/graphicon-2020-2-3-19","url":null,"abstract":"This work is devoted to the application of a generalized computational experiment for a comparative assessment of numerical methods accuracy. A generalized computational experiment allows one to obtain a numerical solution for a class of problems determined by the ranges of defining parameters variation. The approaches to the application of a generalized computational experiment in the presence of a reference solution and in its absence are dis-cussed. An example of constructing error surfaces is given when the solvers of the OpenFOAM software package are compared. The classic inviscid problem of oblique shock wave is used as a basic task. Variations of the key parameters of the problem — the Mach number and angle of attack — are considered. An example of the problem of flow around a cone at an angle of attack with varying Mach number, cone angle and angle of attack is also considered. The concept of an error index is introduced as an integral characteristic of deviations from the exact solution for each solver in the class of problems under consideration.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125229661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}