Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description
The key task of computer vision is the recognition of visual objects in the analysed image. This paper proposes a method of searching for objects in an image, based on the identification of a cluster representation of the query descriptions and the current image of the window with the calculation of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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VSB-Technical University of Ostrava
2023-01-01
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| Series: | Advances in Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://advances.utc.sk/index.php/AEEE/article/view/4661 |
| _version_ | 1797826891462213632 |
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| author | Volodymyr Gorokhovatskyi Iryna Tvoroshenko Oleg Kobylin Nataliia Vlasenko |
| author_facet | Volodymyr Gorokhovatskyi Iryna Tvoroshenko Oleg Kobylin Nataliia Vlasenko |
| author_sort | Volodymyr Gorokhovatskyi |
| collection | DOAJ |
| description | The key task of computer vision is the recognition of visual objects in the analysed image. This paper proposes a method of searching for objects in an image, based on the identification of a cluster representation of the query descriptions and the current image of the window with the calculation of the relevance measure. The implementation of a cluster representation significantly increases the speed of identification or classification of visual objects while maintaining a sufficient level of accuracy. Based on the development of models for the analysis and processing of a set of descriptors of keypoints, we have obtained an effective method for the identification of visual objects. A comparative experiment with the traditional method has been conducted, where a linear search for the nearest descriptor was implemented for identification without using a cluster representation of the description. In the experiment, a speed gain for the developed method has been obtained in comparison with the traditional one by approximately 5.2 times with the same level of accuracy. The method can be used in applied tasks where the time of object identification is critical. The developed method can be applied to search for several objects of different classes. The effectiveness of the method can be increased by varying the values of its parameters and adapting to the characteristics of the data. |
| first_indexed | 2024-04-09T12:39:32Z |
| format | Article |
| id | doaj.art-3b1b5b5ca0e548eca7e5425e531c8a88 |
| institution | Directory Open Access Journal |
| issn | 1336-1376 1804-3119 |
| language | English |
| last_indexed | 2024-04-09T12:39:32Z |
| publishDate | 2023-01-01 |
| publisher | VSB-Technical University of Ostrava |
| record_format | Article |
| series | Advances in Electrical and Electronic Engineering |
| spelling | doaj.art-3b1b5b5ca0e548eca7e5425e531c8a882023-05-14T20:50:14ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192023-01-01211192710.15598/aeee.v21i1.46611191Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image DescriptionVolodymyr Gorokhovatskyi0Iryna Tvoroshenko1Oleg Kobylin2Nataliia Vlasenko3Department of Informatics, Kharkiv National University of Radio Electronics, Nauky Ave. 14, 61166 Kharkiv, UkraineDepartment of Informatics, Kharkiv National University of Radio Electronics, Nauky Ave. 14, 61166 Kharkiv, UkraineDepartment of Informatics, Kharkiv National University of Radio Electronics, Nauky Ave. 14, 61166 Kharkiv, UkraineDepartment of Informatics and Computer Engineering, Simon Kuznets Kharkiv National University of Economics, Nauky Ave. 9-A, 61166 Kharkiv, UkraineThe key task of computer vision is the recognition of visual objects in the analysed image. This paper proposes a method of searching for objects in an image, based on the identification of a cluster representation of the query descriptions and the current image of the window with the calculation of the relevance measure. The implementation of a cluster representation significantly increases the speed of identification or classification of visual objects while maintaining a sufficient level of accuracy. Based on the development of models for the analysis and processing of a set of descriptors of keypoints, we have obtained an effective method for the identification of visual objects. A comparative experiment with the traditional method has been conducted, where a linear search for the nearest descriptor was implemented for identification without using a cluster representation of the description. In the experiment, a speed gain for the developed method has been obtained in comparison with the traditional one by approximately 5.2 times with the same level of accuracy. The method can be used in applied tasks where the time of object identification is critical. The developed method can be applied to search for several objects of different classes. The effectiveness of the method can be increased by varying the values of its parameters and adapting to the characteristics of the data.http://advances.utc.sk/index.php/AEEE/article/view/4661computer visiondetectorhamming metrick-means method. |
| spellingShingle | Volodymyr Gorokhovatskyi Iryna Tvoroshenko Oleg Kobylin Nataliia Vlasenko Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description Advances in Electrical and Electronic Engineering computer vision detector hamming metric k-means method. |
| title | Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description |
| title_full | Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description |
| title_fullStr | Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description |
| title_full_unstemmed | Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description |
| title_short | Search for Visual Objects by Request in the Form of a Cluster Representation for the Structural Image Description |
| title_sort | search for visual objects by request in the form of a cluster representation for the structural image description |
| topic | computer vision detector hamming metric k-means method. |
| url | http://advances.utc.sk/index.php/AEEE/article/view/4661 |
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