Automatic classification of manga characters using density-based clustering

Hideaki Yanagisawa*, Kengo Kyogoku, Jain Ravi, Hiroshi Watanabe

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Manga (Japanese comic) is a globally popular content. In recent years, sales of e-comics that converted to electronic data from paper-based manga are increasing because of the widespread use of electronic terminals. Against this background, it has been proposed to improve the accessibility of e-comics by tagging manga images with metadata. In order to allocate metadata more efficiently, technology that automatically extracts elements such as character and speech is required. One way to classify characters is to get image features from the character's faces and cluster them. Previous research has shown that using the intermediate output of CNN which fine-tuned with character face images is effective for character face recognition. We proposed a clustering method using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to classify character face images without specifying the number of clusters. However, DBSCAN is greatly affected by the hyperparameter. The purpose of this study is to automatically classify character face images without complicated hyperparameter setting. We examine the application of Ordering Points to Identify the Clustering Structure (OPTICS) and Hierarchical DBSCAN (HDBSCAN), which are density-based clustering algorithms that extend DBSCAN. OPTICS is an algorithm for finding clusters in spatial data, and HDBSCAN is an algorithm extracts flat partition from hierarchical cluster data. We also verify the effective CNN model as the feature extractor of face images. Experimental results showed that HDBSCAN is effective for character face image clustering.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Imaging Technology, IWAIT 2020
EditorsPhooi Yee Lau, Mohammad Shobri
ISBN (Electronic)9781510638358
Publication statusPublished - 2020
EventInternational Workshop on Advanced Imaging Technology, IWAIT 2020 - Yogyakarta, Indonesia
Duration: 2020 Jan 52020 Jan 7

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceInternational Workshop on Advanced Imaging Technology, IWAIT 2020


  • Clustering
  • Density-based
  • Manga

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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