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Dataset of Batik Nitik Sarimbit 120.

Agus Eko Minarno1,2, Indah Soesanti1, Hanung Adi Nugroho1

  • 1Department of Electrical and Information Engineering, Universitas Gadjah Mada, Indonesia.

Data in Brief
|July 25, 2024
PubMed
Summary
This summary is machine-generated.

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The Batik Nitik Sarimbit 120 dataset offers 120 Indonesian batik motif pairs for machine learning. This resource aids in generating new batik patterns, preserving cultural heritage through digital innovation.

Area of Science:

  • Cultural Heritage Studies
  • Computer Vision
  • Digital Art

Background:

  • Batik is a significant Indonesian cultural heritage, embodying rich traditions and philosophical narratives.
  • Existing digital resources for batik motifs are limited, hindering research and digital preservation.
  • The Nitik Sarimbit style represents a specific, important category within Indonesian batik art.

Purpose of the Study:

  • To introduce and describe the Batik Nitik Sarimbit 120 dataset.
  • To provide a comprehensive resource for the study and digital generation of batik patterns.
  • To facilitate machine learning applications in preserving and innovating Indonesian batik heritage.

Main Methods:

  • Curated a dataset of 120 Nitik Sarimbit batik motif pairs from 60 distinct categories.
Keywords:
ArtAutoencoderBatikDiffusionGenerative adversarial networkHeritageNitik

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  • Sourced high-quality images from original fabric samples originating from Yogyakarta, Indonesia.
  • Organized the dataset for use in training and validating machine learning algorithms, including generative methods.

    • Main Results:

    • The Batik Nitik Sarimbit 120 dataset is now available, comprising 120 motif pairs across 60 categories.
    • The dataset enables detailed analysis and exploration of Nitik Sarimbit batik patterns.
    • Facilitates the development of generative models for creating novel batik designs.

    Conclusions:

    • The Batik Nitik Sarimbit 120 dataset is a valuable resource for researchers, artists, and cultural institutions.
    • This dataset supports the preservation and promotion of Indonesian batik heritage through digital scholarship.
    • It opens new possibilities for innovation in batik art using machine learning and generative techniques.