Pattern Recognition and Image Analysis Journal Impact Factor & Information

Publisher: Nauchnyĭ sovet po kompleksnoĭ probleme "Kibernetika" (Akademii︠a︡ nauk SSSR), MAIK Nauka/Interperiodica

Journal description

Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications is an international journal featuring top papers in pattern recognition, image recognition, analysis, understanding, and processing. The Editorial Board is headed by Yuri Zhuravlev, a prominent Russian mathematician, Full Member of the Russian Academy of Sciences. The board also includes distinguished scientists and engineers from the Russian Academy of Sciences, CIS universities and industry, as well as internationally recognized experts in the field from the USA and Europe. The authors are experts in research and applications. Emphasis is made on rapid publishing of concise articles covering theory, methodology, and practical applications. Major topics include mathematical theory of pattern recognition, raw data representation, computer vision, image processing, machine learning, computer graphics, data and knowledge bases, neural nets, software, specialized computer architectures, applications, and related areas.

Current impact factor: 0.00

Impact Factor Rankings

Additional details

5-year impact 0.00
Cited half-life 0.00
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.00
Website Pattern Recognition and Image Analysis website
Other titles Raspoznavanie obrazov i analiz izobrazheniĭ
ISSN 1054-6618
OCLC 60627519
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

MAIK Nauka/Interperiodica

  • Pre-print
    • Archiving status unclear
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • On author or institutional server only
    • On a non-profit server
    • Publisher copyright and source must be acknowledged
    • Must link to publisher's website
  • Classification
    ​ blue

Publications in this journal

  • Pattern Recognition and Image Analysis 01/2016;
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    ABSTRACT: This paper presents a distributed framework for multi-object tracking which deals with complex static and dynamic occlusions in visual-surveillance crowded scenes. Multiple autonomous particle filters are used for multi-object tracking in which each filter tracks a specific object. Stop-and-Go technique based on inter-blobs management, graph matching and a model of the scene is proposed for handling complex occlusions and inter-particle coalescence problems. The proposed technique is embedded into each autonomous filter to perform multi-object tracking in real time with linear complexity in terms of the number of the tracked objects. Experimental results in challenging surveillance sequences demonstrate the robustness of the proposed framework.
    Pattern Recognition and Image Analysis 04/2015; 25(2). DOI:10.1134/S1054661815020042
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    ABSTRACT: The trabecular bone microarchitecture is used by radiologists for visual bone diseases diagnostics. So the possibility of the automated computer diagnostics of the digital radiograms was studied. A number of textural features were examined to select the most efficient group for the diagnostic. Plain hip radiograms of 42 patients were used for both BMD measure and textural features evaluation. For the features efficiency assessment both the variance analysis and the correlation analysis were used. Also the efficiency was validated experimentally by the diagnostic error probability assessment. It was found that the most efficient features are the covariance features—they provide diagnostic error probability 0.2. Also there was a significant correlation (0.6) between some Gabor spectral features and the Singh Index performed by the radiologists.
    Pattern Recognition and Image Analysis 04/2015; 25(2):301-305. DOI:10.1134/S1054661815020108
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    ABSTRACT: The properties of operators with finite memory in terms of their application for measurement-smoothing processing and detection of image brightness-change boundaries are investigated. Examples of forming operators with given properties and examples of their application to processing real images are viewed.
    Pattern Recognition and Image Analysis 04/2015; 25(2):230-236. DOI:10.1134/S1054661815020194
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    ABSTRACT: A geoinformation system for the agriculture sector of Samara region for the statistical accounting and analysis of agricultural lands is examined in this paper. The architecture of a geoinformation system and its main functions are described. Space monitoring for a sown area is a problem solved by the system. A detailed description of satellite monitoring stages is given in the paper. A method to classify agricultural fields according to crop types by using a time series for the vegetation index NDVI is examined, and its application for observing the results of spring and autumn sowing are presented for the Samara region.
    Pattern Recognition and Image Analysis 04/2015; 25(2):347-353. DOI:10.1134/S1054661815020261
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    ABSTRACT: This paper discusses quality metrics as well as procedure for parameters optimization and model assessment for human activity recognition based on sensors signals. We compare micro and macro performance measures in multiclass classification as well as various cross-validation techniques. The paper introduces general concept of Dual Leave-Group-of-Sources-Out cross-validation procedure. This technique provides reliable way for model parameters optimization in practical applications and prevents overestimation of recognition quality from point of view generalization capability.
    Pattern Recognition and Image Analysis 04/2015; 25(2):263-269. DOI:10.1134/S1054661815020224
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    ABSTRACT: A detailed overview is given of an ontological spatial monitoring system (OSMS) based on the multiagent approach to complex tasks and focused on the end user. The main benefits of the combined use of the ontological and multiagent approaches are discussed. Agricultural land monitoring is used as an example to consider the main aspects involved in designing a team of agents engaged in the monitoring of spatial objects.
    Pattern Recognition and Image Analysis 04/2015; 25(2):201-208. DOI:10.1134/S1054661815020054
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    ABSTRACT: In this paper, real-time algorithms for segmentation and detection of contrast objects in color images are proposed, which provide stable segmentation components for solving scene recognition problems. The selected contrast objects are approximately described using the graph of structural color bunches STG introduced by the author. A bipartite graph LRG of left and right contrast boundary curves (germs of global objects) in STG is attached to each image. Connected components in LRG are candidates for contrast objects in STG. Constructing algorithms are based on the geometrized histogram method developed by the author. The detection of stable segmentation components in images is applied to analysis of video sequences in order to find visual landmarks. Applications of the developed technique to autonomous navigation of robots are dicussed.
    Pattern Recognition and Image Analysis 04/2015; 25(2):338-346. DOI:10.1134/S1054661815020145
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    ABSTRACT: Hevea (Rubber tree) leaf characteristics have not been utilized yet for automation systems to classify different clones. However rubber tree leaves have some features that can be used to differentiate the clones. The rubber tree leaf is in the class of palmate leaves which means three leaflets are joined at one mutual base. This unique feature gives different positions of the leaflets whether the leaves are overlapping or separated that it can distinguish a particular clone from all other clones. This paper focuses on the position of leaflets in order to identify leaf boundaries. The proposed framework is producing satisfactory results to identify the rubber tree leaf boundaries.
    Pattern Recognition and Image Analysis 04/2015; 25(2):291-294. DOI:10.1134/S1054661815020029
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    ABSTRACT: In this paper, Multi-Class T-Weight Method (MCTW) is presented for classification in brain-computer interface (BCI) systems. Proposed method is an extension of the existing Improved T-Weight method for multi-class problems. The method was tested on the frequency and correlation based features obtained from electroencephalogram data of 20 Subjects in a steady state visual evoked potential (SSVEP) based offline BCI classification task. Obtained classification performances with different classifiers show that the MCTW method compete with the other well-known classifiers like linear discriminant analysis (LDA) and support vector machines (SVMs). Therefore, it can be used in classifying SSVEP based electroencephalogram data with proper features.
    Pattern Recognition and Image Analysis 04/2015; 25(2):321-326. DOI:10.1134/S1054661815020121
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    ABSTRACT: The research area of this article lies at the junction of the instrument-making industry and gas dynamics and covers a scope of problems, related to designing the optimal software-hardware architecture for processing data from physical experiments. The work concerns experiments on investigations of highspeed continuous spin detonation processes. The velocity of the detonation wave exceeds the velocity of sound in the medium by dozens of times. A photosensitive line that supports sufficiently high velocities is quite suitable for the optimal video filming of similar processes. However, for working with the resultant data stream it is required to design a software-hardware complex equipped with a largevolume random access memory that implements the controller of the available memory. For this purpose, a device allowing an optimal solution of the formulated problems was created. The paper describes turning points in designing the unit and the experimental results obtained during the final adjustment of the unit.
    Pattern Recognition and Image Analysis 04/2015; 25(2):255-262. DOI:10.1134/S1054661815020236
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    ABSTRACT: The process of scanning a focused light beam by a metal-coated fiber probe with a subwavelength aperture is simulated using the finite element method for the two- and three-dimensional cases. Intensity pictures of a focal spot are obtained. For various configurations of the probes, sensitivity to electromagnetic components is investigated. Qualitative differences in the results of the two- and three-dimensional simulation are discussed. In the two-dimensional case, the probe response is found to be independent of the aperture size. However, in the three-dimensional case, the probe response depends heavily on the aperture diameter.
    Pattern Recognition and Image Analysis 04/2015; 25(2):306-313. DOI:10.1134/S1054661815020078
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    ABSTRACT: A mobile computer vision system for real-time biometric hand-based identification is presented in the paper. This system is characterized by a flexible client-server architecture and a simple interface for interaction with the end user. It may be implemented on any mobile device under Android operating system version 4.0 or higher with an integrated camera and Internet access. The designed system was applied for collecting a hand database with further field testing. To solve identification problems, a continuous skeleton approach was used, which showed satisfactory results, and may thus be applicable as a part of a more complex multimodal classification scheme of hands (objects) by people (classes).
    Pattern Recognition and Image Analysis 04/2015; 25(2):209-214. DOI:10.1134/S1054661815020066
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    ABSTRACT: Various approaches to solving the problem of filtration of a continuous periodic signal distorted by stationary additive noncorrelated noise are considered. The case when the known signal period is not divisible by the signal sampling interval requires special attention.
    Pattern Recognition and Image Analysis 04/2015; 25(2):161-166. DOI:10.1134/S105466181502008X
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    ABSTRACT: Algorithms for procedural generation are proposed that make it possible to automate the creation of 3D models of floor plans and objects of the internal structure of buildings and facilities. Various techniques to optimize the visualization process are given. The combined use of these techniques makes it possible to show highly detailed 3D models of objects of the internal structure of buildings and facilities in real time.
    Pattern Recognition and Image Analysis 04/2015; 25(2):278-280. DOI:10.1134/S105466181502025X
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    ABSTRACT: The paper considers the problem of the segmentation of microscopy images of blood cells, its solution being the first stage of an automated analysis of a blood smear image. The applicability for this purpose of several well-known methods of image segmentation is assessed, and a segmentation method employing some elements of these techniques is suggested. The approach proposed includes such steps as edge detection, contour closing, and oversegmentation elimination (based on a feature set calculated for every segment).
    Pattern Recognition and Image Analysis 04/2015; 25(2):167-173. DOI:10.1134/S1054661815020169
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    ABSTRACT: This paper is devoted to the problem of textual information transfer between experts and trainees in a computer-aided system for learning and testing of knowledge. A method is developed for the revelation of a semantic standard in a language usage situation (LUS) on the basis of word clustering by the occurrence frequency in semantically equivalent (SE) phrases in natural language (NL). An approach is presented to the revelation of stems and inflections in a word through the analysis of the occurrence frequency of letters in different positions with respect to the beginning and end of a word in the context of a LUS. An algorithm is developed for the extraction of structural units that correspond to syntagmas and determine the lexico-syntactic relations within a feature description of a LUS.
    Pattern Recognition and Image Analysis 04/2015; 25(2):223-229. DOI:10.1134/S1054661815020170
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    ABSTRACT: A new approach to the synthesis of dynamical systems with given properties is presented that is based on the statement of a synthesis problem as a pattern recognition problem with active experiment and its solution by the methods of data mining. The need for the development of a new approach has been called forth by the laboriousness, and often by the impossibility to solve this topical problem during the synthesis of dynamical systems of sufficiently large dimension and with a large number of parameters. The specific features of the statement and solution of this problem are illustrated by an example of the synthesis of quasi-invariant control systems.
    Pattern Recognition and Image Analysis 04/2015; 25(2):270-277. DOI:10.1134/S1054661815020248
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    ABSTRACT: Order filters possess a number of advantages. However such filters are related to nonlinear ones and therefore their analytical projection and the analysis of their behavior are rather complicated. This depends both on the kind of signal and on the character of noise in each concrete case. The given circumstance allows us to consider the project of an order filter as a casual event defining the quality of processing a signal. At the same time, the peculiarity of the standard order filter is that the response of the filter tends to zero as the filter length approaches signal period. In this paper a technique for the adaptation of order filters for the processing of periodic and frequency-modulated signals using a graphical interface is offered.
    Pattern Recognition and Image Analysis 04/2015; 25(2):281-290. DOI:10.1134/S1054661815020273