IMAGE SEGMENTATION AND OBJECT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORK TECHNOLOGY
| Autor: | Yu. A. Gagarin, P.S. Egorov, A.I. Godunov, S.T. Balanyan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science segmentation Cognitive neuroscience of visual object recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION bernsen's method convolutional neural network Pattern recognition TL1-4050 General Medicine Image segmentation Convolutional neural network threshold methods savol's method Artificial intelligence business adaptive methods otsu's method niblack's method Motor vehicles. Aeronautics. Astronautics |
| Zdroj: | Надежность и качество сложных систем, Iss 3 (2021) |
| ISSN: | 2307-4205 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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