Using Machine Learning and Generative Intelligence in Book Cover Development.

IF 2.7 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Journal of Imaging Pub Date : 2025-02-07 DOI:10.3390/jimaging11020046
Nonna Kulishova, Daiva Sajek
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Abstract

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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在书籍封面开发中使用机器学习和生成智能。
机器学习和人工智能方法的快速发展在生活的各个领域得到了越来越广泛的应用。本文考虑了在使用机器学习和生成式人工智能(GAI)方法设计图书封面时改进编辑和出版过程(即自出版)的问题。在选择一本书时,读者通常对出版物的设计有一定的期望,包括封面的颜色。这些期望可以被称为颜色偏好,它们可以取决于书的类型,它的目标受众,甚至个人联想。文化背景也会影响颜色的选择,因为在不同的文化中,某些颜色可以象征不同的情感或情绪。对同一类型的书籍封面图像进行聚类分析,可以识别出该类型固有的颜色偏好,建议在设计新封面时使用。生成服务的能力,创造和改进封面设计也进行了调查。提出了一种改进的自出版图书封面设计GAI流程,其中增加了探索、调节、演进三个阶段。在这些阶段,设计师为GAI创建提示,并检查它们和GAI的问题如何与任务相对应。条件作用允许更精确地调整提示,以适应每本书的特点,并且进化阶段还包括已经从GAI收到的结果的后处理。反过来,后处理既可以在生成服务中执行,也可以由设计人员执行。该实验允许我们使用机器学习方法来确定哪种颜色在某一类型的书籍封面布局中最常见,并检查这些颜色是否与和谐的调色板相对应。根据提出的使用生成式人工智能的设计过程方案,获得给定体裁的图书封面版式版本。
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来源期刊
Journal of Imaging
Journal of Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.90
自引率
6.20%
发文量
303
审稿时长
7 weeks
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