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Packaging Design Based on Deep Learning and Image Enhancement
Packaging design is an important part of product design. How to improve the efficiency of packaging design is a problem that must be considered in product design. Existing packaging design methods require a lot of human and material resources. In view of this situation, this paper proposes a packagi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365577/ https://www.ncbi.nlm.nih.gov/pubmed/35965777 http://dx.doi.org/10.1155/2022/9125234 |
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author | Liu, Jinping |
author_facet | Liu, Jinping |
author_sort | Liu, Jinping |
collection | PubMed |
description | Packaging design is an important part of product design. How to improve the efficiency of packaging design is a problem that must be considered in product design. Existing packaging design methods require a lot of human and material resources. In view of this situation, this paper proposes a packaging design method based on deep learning. This paper innovatively proposes a packaging design model based on deep convolution generative adversarial networks (DCGAN). This paper constructs a dataset of packaging design schemes and trains the proposed DCGAN model. The results show that the packaging design generated by the model proposed in this paper can get a score similar to that of the expert design scheme, which proves the effectiveness and rationality of the proposed model. In addition, in order to further improve the imaging quality of packaging design images, this paper proposes a packaging design image enhancement method based on visual communication technology. The packaging design image enhancement processing is carried out through the guided filtering method, and the visual communication optimization and edge pixel fusion methods are used to decompose the multidimensional scale features of the packaging design image under the visual communication technology to realize the packaging design image enhancement processing. The simulation results show that the method used for packaging design image enhancement processing has better visual communication ability, higher degree of image information fusion, and improved packaging design effect. |
format | Online Article Text |
id | pubmed-9365577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93655772022-08-11 Packaging Design Based on Deep Learning and Image Enhancement Liu, Jinping Comput Intell Neurosci Research Article Packaging design is an important part of product design. How to improve the efficiency of packaging design is a problem that must be considered in product design. Existing packaging design methods require a lot of human and material resources. In view of this situation, this paper proposes a packaging design method based on deep learning. This paper innovatively proposes a packaging design model based on deep convolution generative adversarial networks (DCGAN). This paper constructs a dataset of packaging design schemes and trains the proposed DCGAN model. The results show that the packaging design generated by the model proposed in this paper can get a score similar to that of the expert design scheme, which proves the effectiveness and rationality of the proposed model. In addition, in order to further improve the imaging quality of packaging design images, this paper proposes a packaging design image enhancement method based on visual communication technology. The packaging design image enhancement processing is carried out through the guided filtering method, and the visual communication optimization and edge pixel fusion methods are used to decompose the multidimensional scale features of the packaging design image under the visual communication technology to realize the packaging design image enhancement processing. The simulation results show that the method used for packaging design image enhancement processing has better visual communication ability, higher degree of image information fusion, and improved packaging design effect. Hindawi 2022-08-01 /pmc/articles/PMC9365577/ /pubmed/35965777 http://dx.doi.org/10.1155/2022/9125234 Text en Copyright © 2022 Jinping Liu. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Jinping Packaging Design Based on Deep Learning and Image Enhancement |
title | Packaging Design Based on Deep Learning and Image Enhancement |
title_full | Packaging Design Based on Deep Learning and Image Enhancement |
title_fullStr | Packaging Design Based on Deep Learning and Image Enhancement |
title_full_unstemmed | Packaging Design Based on Deep Learning and Image Enhancement |
title_short | Packaging Design Based on Deep Learning and Image Enhancement |
title_sort | packaging design based on deep learning and image enhancement |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365577/ https://www.ncbi.nlm.nih.gov/pubmed/35965777 http://dx.doi.org/10.1155/2022/9125234 |
work_keys_str_mv | AT liujinping packagingdesignbasedondeeplearningandimageenhancement |