IMAGE SEGMENTATION AND OBJECT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORK TECHNOLOGY
Background. An analysis of the processes of image segmentation is being carried out. An original method of image segmentation using a convolutional neural network is proposed. Materials and methods. A comparative assessment of existing segmentation methods such as threshold segmentation methods: O...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN RU |
| Publicado: |
Penza State University Publishing House
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4724ca36bfbe461fbf58fbd8179bca2a |
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| Sumario: | Background. An analysis of the processes of image segmentation is being carried out. An original
method of image segmentation using a convolutional neural network is proposed. Materials and methods. A comparative
assessment of existing segmentation methods such as threshold segmentation methods: Otsu, Niblack, Bernsen,
Savola, as well as the method of image segmentation using a convolutional neural network is carried out. Their advantages
and disadvantages are evaluated. Examples of image segmentation by various methods are given. Algorithmic
descriptions of segmentation methods are presented. Experiments were carried out to study the segmentation of
frames (images) from a given video sequence. Results and conclusions. The results of the experiment, showing the operation
of one or another segmentation method, are presented. |
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