Ensuring the invariance of the pattern recognition system of the marine vessel systems in the process of fishing
DOI:
https://doi.org/10.15587/1729-4061.2015.55696Keywords:
digital video information, fish shoal, identification, information system, clusteringAbstract
Analysis of the existing algorithms for processing and transmitting video information for decision-making in information systems has shown that the existing algorithms do not consider the objective identification moments on the fishing fleet vessels. The problems of the impossibility of visualization of real images, clear separation of the object and the background, spatial arrangement of the points in the automated segmentation of digital images are displayed through the dependence by the features of adjacent frames in feature description methods.
This necessitated the development of more detailed algorithms for the digital video data analysis, devoid of these shortcomings.
This method involves the extraction of the contours of the object, which allowed to obtain a set of features and served as a basis for its analysis and recognition. Using the module of the normalized scalar product enabled to effectively solve the basic recognition problems - transfer, rotation and zooming of the object image.
The assessment methods of digital video information were investigated. The main result of this study was the development of a tool for an integrated objective quality assessment of the data transmitted. The feature of the developed tool is that it is integrated into the Scanmar model that allows to simulate the multimedia processing and transmission networks with the assessment of quality losses in real time.
The experiments, conducted using the developed tool, to assess the quality of video encoded by existing compression algorithms have shown that H.264 codec, which showed a higher video quality level than in similar compression by MPEG-4 and MJPEG codecs appears the most effective.
References
- Duda, R. K. (1976). Raspoznavanye obrazov y analyz stsen. Moscow: Myr, 511.
- Bravermana, Е. M. (1969). Avtomatycheskyi analyz slozhnykh izobrazhenyi. Moscow: Nauka, 310.
- Tu, Dzh., Honsales, R. (1978). Pryntsypy raspoznavanyia obrazov. Moscow: Myr, 416.
- Honzales, P., Vuds, P., Eddyns, S. (2006). Tsyfrovaia obrabotka izobrazhenyi v srede MATLAB. Moscow: Tekhnosfera, 616.
- Vasylev, K. K., Tashlynskyi A. N. (1998). Otsenka parametrov deformatsyy mnohomernkh yzobrazhenyi, nabliudaemkh na fone pomekh. Trudy NTK ROAY-4. Novosibirsk, 261–264.
- Forsait, D. Pons, Zh. (2004). Kompiuternoe zrenye. Sovremennyi podkhod. Moscow: Vyliams, 928.
- Diukova, E. V., Peskov, N. V. (2002). Poisk informativnykh fragmentov opisanii obektov v diskretnykh protsedurakh raspoznavaniia. Vychislitelnaia matematika i matematichskaia fizika, 42 (5), 741–753.
- Hertz, T., Bar-Hillel, A., Weinshall, D. (2004). Boosting Margin Based Distance Functions for Clustering. Proceedings of the twenty-first international conference on Machine learning. New York, 50. doi: 10.1145/1015330.1015389
- Rozenfeld, A. (1987). Raspoznavanye i obrabotka izobrazhenii. Moscow: Myr, 274.
- Khemming, R. V. (1990). Tsyfrovye filtry. Moscow: Nauka, 268.
- SCANMAR. Available at: http://www.scanmar.no/en/Manuals/
- Chernyi, S. G., V. Yu. Budnik, (2015). Elements of the introspective analysis to evaluate software in navigation. Proceedings 22nd International Conference on Integrated Navigation Systems ICINS 2015. Saint Petersburg, 147–150.
- Zhang, D., Lu, G. (2003). A comparative study of curvature scale space and Fourier descriptors for shape-based image retrieval. Journal of Visual Communication and Image Representation, 14 (1), 39–57. doi: 10.1016/s1047-3203(03)00003-8
- Chernyi, S. (2015). The implementation of technology of multi-user client-server applications for systems of decision making support. Metallurgical and Mining Industry, 3, 60–65.
- Zhilenkov, A., Chernyi, S. (2015). Investigation performance of marine equipment with specialized information technology. Energy Procedia, 100, 1247–1252. doi: 10.1016/j.proeng.2015.01.490
- Chernyi, S. Zhilenkov, A. (2015). Analysis of complex structures of marine systems with attraction methods of neural systems. Metallurgical and Mining Industry, 1, 37–44.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2015 Александр Александрович Железняк, Юрий Федорович Каторин, Надежда Павловна Сметюх, Владимир Алексеевич Доровской, Сергей Григорьевич Черный
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.
