Fips: an OpenGL based FITS viewer
FITS (Flexible Image Transport System) is a common format for astronomical data storage. It was first standardised in the early 1980s. Even though astronomical data is now processed mostly using software, visual data inspection by a human is still important during equipment or software commissioning and while observing. We present Fips, a cross-platform FITS file viewer open source software. To the best of our knowledge, it is for the first time that the image rendering algorithms are implemented mostly on GPU (graphics processing unit). We show that it is possible to implement a fully-capable FITS viewer using OpenGL interface. We also emphasise the advantages of using GPUs for efficient image handling.
This book constitutes the proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018, held in Moscow, Russia, in July 2018.
The 29 full papers were carefully reviewed and selected from 107 submissions (of which 26 papers were rejected without being reviewed). The papers are organized in topical sections on natural language processing; analysis of images and video; general topics of data analysis; analysis of dynamic behavior through event data; optimization problems on graphs and network structures; and innovative systems.
The Cropland Capture game (CCG) aims to map cultivated lands using around 170000 satellite images. The contribution of the paper is threefold: (a) we improve the quality of the CCG’s dataset, (b) we benchmark state-of-the-art algorithms designed for an aggregation of votes in a crowdsourcing-like setting and compare the results with machine learning algorithms, (c) we propose an explanation for surprisingly similar accuracy of all examined algorithms. To accomplish (a), we detect image duplicates using the perceptual hash function pHash. In addition, using a blur detection algorithm, we filter out unidentifiable images. In part (c), we suggest that if all workers are accurate, the task assignment in the dataset is highly irregular, then state-of-the-art algorithms perform on a par with Majority Voting. We increase the estimated consistency with expert opinions from 77% to 91% and up to 96% if we restrict our attention to images with more than 9 votes.
The paper sets out one of the methodologies on image processing and recognition of the form of graphic objects. In it, at the first stage preliminary processing of the image with the purpose of extracting of characteristic attributes of the form of objects is made. Contours of objects are used as such attributes. For transformation of 2D contours of objects to one-dimensional contour function ArcHeight method has been used. The algorithm for identification contour functions based on metrics DTW is developed. Definition of the identification function based on this method is introduced. Features of application of metrics DTW are stated at identification of the form of objects. Matrices of distances of combinations the sample-sample and the sample-not sample are presented. Results of calculations of metrics DTW on a plenty of real data are analyzed. It is shown, that the developed algorithm allows to identify the form of objects independently of their position and an angle of turn on the image. Influence of the noise imposed on the image of object, on value of the metrics is investigated. Theoretical and practical results of such dependence are received; it shows that in a wide range (up to the ratio a signal/noise 10 dB) value of the metrics practically does not change. The positive parties and lacks of the offered algorithm are noted at identification of the form of object.
In the paper we present a new notion of stochastic monotone measure and its application to image processing. By definition, a stochastic monotone measure is a random value with values in the set of monotone measures and it can describe a choice of random features in image processing. In this case, a monotone measure describes uncertainty in the problem of choosing the set of features with the highest value of informativeness and its stochastic behavior is explained by a noise that can corrupt images.
On the basis of the signature analysis it is entered various concepts: the sample containing information and procedural parts and contour function. The identification methodology graphic objects invariant to affine transformations on the basis of concept of contour function is stated.
System of image processing of undermost biological object, to permit calculate their geometric parameters in process of morphogenesis was designed. We propose criterion on which base it is possible to calculate velocities of regenerations of the lost parts from ?at worms-planaria.
This book constitutes the refereed proceedings of the 9th International Conference on Optimization and Applications, OPTIMA 2018, held in Petrovac, Montenegro, in October 2018.
The 35 revised full papers and the one short paper presented were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections on mathematical programming; combinatorial and discrete optimization; optimal control; optimization in economy, finance and social sciences; applications.
This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.