Using Machine Learning and Generative Intelligence in Book Cover Development

The rapid development of machine learning and artificial intelligence approaches is finding ever wider application in various areas of life. This paper considers the problem of improving editorial and publishing processes, namely self-publishing, when designing book covers using machine learning and...

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Main Authors: Nonna Kulishova, Daiva Sajek
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Journal of Imaging
Subjects:
Online Access:https://www.mdpi.com/2313-433X/11/2/46
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author Nonna Kulishova
Daiva Sajek
author_facet Nonna Kulishova
Daiva Sajek
author_sort Nonna Kulishova
collection DOAJ
description The rapid development of machine learning and artificial intelligence approaches is finding ever wider application in various areas of life. This paper considers the problem of improving editorial and publishing processes, namely self-publishing, when designing book covers using machine learning and generative artificial intelligence (GAI) methods. When choosing a book, readers often have certain expectations regarding the design of the publication, including the color of the cover. These expectations can be called color preferences, and they can depend on the genre of the book, its target audience, and even personal associations. Cultural context can also influence color choice, as certain colors can symbolize different emotions or moods in different cultures. Cluster analysis of book cover images of the same genre allows us to identify color preferences inherent in the genre, which is proposed to be used when designing new covers. The capabilities of generative services for creating and improving cover designs are also investigated. An improved flow chart for using GAI in creating book covers in the process of self-publishing is proposed, which includes new stages, namely exploring, conditioning, and evolving. At these stages, the designer creates prompts for GAI and examines how they and GAI’s issuances correspond to the task. Conditioning allows for even more precise adjustment of prompts to features of each book, and the evolving stage also includes post-processing of results already received from GAI. Post-processing, in turn, can be performed both in generative services and by a designer. The experiment allowed us to use the machine-learning method to determine which colors are most often found in book cover layouts of one of the genres and to check whether these colors correspond to harmonious color palettes. In accordance with the proposed scheme of the design process using generative artificial intelligence, versions of book cover layouts of a given genre were obtained.
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spelling doaj-art-803f01dab6914a0eab3bed4fd0e415e42025-08-20T03:12:22ZengMDPI AGJournal of Imaging2313-433X2025-02-011124610.3390/jimaging11020046Using Machine Learning and Generative Intelligence in Book Cover DevelopmentNonna Kulishova0Daiva Sajek1Kauno Kolegija Higher Education Institution, Faculty of Informatics, Engineering and Technologies, Pramonés av. 20, 111965284 Kaunas, LithuaniaKauno Kolegija Higher Education Institution, Faculty of Informatics, Engineering and Technologies, Pramonés av. 20, 111965284 Kaunas, LithuaniaThe rapid development of machine learning and artificial intelligence approaches is finding ever wider application in various areas of life. This paper considers the problem of improving editorial and publishing processes, namely self-publishing, when designing book covers using machine learning and generative artificial intelligence (GAI) methods. When choosing a book, readers often have certain expectations regarding the design of the publication, including the color of the cover. These expectations can be called color preferences, and they can depend on the genre of the book, its target audience, and even personal associations. Cultural context can also influence color choice, as certain colors can symbolize different emotions or moods in different cultures. Cluster analysis of book cover images of the same genre allows us to identify color preferences inherent in the genre, which is proposed to be used when designing new covers. The capabilities of generative services for creating and improving cover designs are also investigated. An improved flow chart for using GAI in creating book covers in the process of self-publishing is proposed, which includes new stages, namely exploring, conditioning, and evolving. At these stages, the designer creates prompts for GAI and examines how they and GAI’s issuances correspond to the task. Conditioning allows for even more precise adjustment of prompts to features of each book, and the evolving stage also includes post-processing of results already received from GAI. Post-processing, in turn, can be performed both in generative services and by a designer. The experiment allowed us to use the machine-learning method to determine which colors are most often found in book cover layouts of one of the genres and to check whether these colors correspond to harmonious color palettes. In accordance with the proposed scheme of the design process using generative artificial intelligence, versions of book cover layouts of a given genre were obtained.https://www.mdpi.com/2313-433X/11/2/46generative artificial intelligencemachine learningk-meansclusteringcolorbook covers
spellingShingle Nonna Kulishova
Daiva Sajek
Using Machine Learning and Generative Intelligence in Book Cover Development
Journal of Imaging
generative artificial intelligence
machine learning
k-means
clustering
color
book covers
title Using Machine Learning and Generative Intelligence in Book Cover Development
title_full Using Machine Learning and Generative Intelligence in Book Cover Development
title_fullStr Using Machine Learning and Generative Intelligence in Book Cover Development
title_full_unstemmed Using Machine Learning and Generative Intelligence in Book Cover Development
title_short Using Machine Learning and Generative Intelligence in Book Cover Development
title_sort using machine learning and generative intelligence in book cover development
topic generative artificial intelligence
machine learning
k-means
clustering
color
book covers
url https://www.mdpi.com/2313-433X/11/2/46
work_keys_str_mv AT nonnakulishova usingmachinelearningandgenerativeintelligenceinbookcoverdevelopment
AT daivasajek usingmachinelearningandgenerativeintelligenceinbookcoverdevelopment