Investigation of the applicability of natural language processing methods to problems of searching and matching of machinery drawing images

Проведенные в работе исследования показывают, что применение технологии дескрипторов особых точек в чистом виде к задаче сравнения и поиска чертежей является неэффективным. Выявлено, что основной причиной этому служит наличие в чертежах большого количества идентичных элементов (рамки, основная надпись, выносные линии, элементы шрифтов и др.). Для решения данной проблемы предложено использование метода tf-idf (term frequency-inverse document frequency), широко известного в технологии обработки естественного языка. В исследовании вместо векторов слов, применяемых в оригинальной методике tf-idf, использовались дескрипторы особых точек изображений, вычисленных по алгоритмам ORB и BRISK. В результате исследования получены следующие выводы: 1) показана высокая эффективность предлагаемого подхода для поиска копии изображения-запроса в базе данных. Так, для всех изображений, предложенных для поиска и имеющих свои полные аналоги в базе данных, было выявлено наличие копий. 2) Количество выявленных изображений, являющихся модификациями изображения-запроса, разнится и зависит от алгоритма нахождения особых точек и дескрипторов. Так, при использовании ORB максимальное количество выявленных модифицированных аналогов составило 60%, при использовании BRISK – 80% от всех аналогов изображения, находящихся в базе данных. 3) Предлагаемый подход показывает ограниченную эффективность для нахождения изображений, которые можно отнести к тому же классу, что и изображение-запрос (например, чертеж экскаватора, бульдозера, автомобильного крана). Здесь максимальное количество ложных определений достигло 60%

Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

The study of low-dimensional, noisy manifolds embedded in a higher dimensional space has been extremely useful in many applications, from the chemical analysis of multi-phase flows to simulations of galactic mergers. Building a probabilistic model of the manifolds has helped in describing their essential properties and how they vary in space. However, when the manifold is evolving through time, a joint spatio-temporal modelling is needed, in order to fully comprehend its nature. We propose a first-order Markovian process that propagates the spatial probabilistic model of a manifold at fixed time, to its adjacent temporal stages. The proposed methodology is demonstrated using a particle simulation of an interacting dwarf galaxy to describe the evolution of a cavity generated by a Supernov

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

Distributed Anti-Plagiarism Checker for Biomedical Images Based on Sensor Noise

The increasing number of scientific papers reporting false or stolen data calls for the needs of new tools able to automatically detect plagiarism or unfaithful ownerships. This problem is particularly actual for the health sciences, as the number of biomedical images that are stolen or manipulated and, then, published in scientific papers is becoming higher and higher [1]. In this paper we present an automatic anti-plagiarism checker that relies on the concept of Pixel Non-Uniformity (PNU) noise. This is the characteristic noise left by source sensors of devices like digital cameras, electron microscopes or Magnetic Resonance Imaging (MRI) to define a sort of fingerprint for these devices. The intended use of our system requires two steps. In a first step and on a voluntary base, the researchers register to the system their imaging devices by providing a training set of images. These will be used to extract the device fingerprint called Reference Pattern (RP). In a second step, the system will periodically scan a set of known scientific digital libraries (most publishers offer on-line access to their papers) downloading the new papers and extracting all the images herein contained. The output produced by a specialized filter on such images will enable the system to compare the Residual Noise (RN) with all the enrolled device patterns, allowing the identification of the device that captured the image. Given the huge amount of papers and images to process, our system has been implemented as a distributed application running on top of the Spark cluster engine