Manga character clustering with DBSCAN using fine-tuned CNN model

Hideaki Yanagisawa, Takuro Yamashita, Watanabe Hiroshi

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

2 Citations (Scopus)


Manga (Japanese comic) is popular content worldwide. In Japan, e-comic accounts for about 80% of e-book market. In recent years, metadata extraction from manga image has been studied for providing e-comic service. Manga character is one of the important contents for story understanding. In conventional research, some character identification methods are proposed those classify characters' face images using k-means clustering. However, there are two problems. First, kmeans method needs to specify the number of clusters, however the number of characters in target manga images is commonly unknown. Second, manga includes characters with few appearing, so it is difficult to classify characters with high purity. To solve these problems, we propose clustering method using DBSCAN which decides number of clusters automatically and is robust to noise data. In our prior research, it is experimented that character face clustering using DBSCAN and general CNN features. However, general CNN model is difficult to capture detailed features of manga characters. In this paper, we apply DBSCAN to fine-tuned CNN with manga character faces to improve the clustering accuracy. We also compare the optimal parameter determination method of DBSCAN. Experimental results showed that the dimensional reduction using Kernel PCA and UMAP is effective. In addition, we confirmed the validity of proposed method that determining the parameters of DBSCAN based on the slope changing of k-distance graph.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Image Technology, IWAIT 2019
EditorsYung-Lyul Lee, Sanun Srisuk, Qian Kemao, Wen-Nung Lie, Kazuya Hayase, Lu Yu, Phooi Yee Lau
ISBN (Electronic)9781510627734
Publication statusPublished - 2019
EventInternational Workshop on Advanced Image Technology 2019, IWAIT 2019 - Singapore, Singapore
Duration: 2019 Jan 62019 Jan 9

Publication series

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


ConferenceInternational Workshop on Advanced Image Technology 2019, IWAIT 2019


  • CNN
  • clustering
  • 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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