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This dataset presents an in-depth AI-assisted comparative analysis between Vincent van Gogh’s Undergrowth with Two Figures (1890) and The Tree Oil Painting (undated, unattributed). The objective is to examine whether both works share measurable consistencies in brushstroke behavior, energy dynamics, and structural execution.

Developed and analyzed by HaruthaiAI (May 2025), this dataset employs 18 advanced AI forensic techniques including Canny edge detection, Gabor filtering, Fourier transform, torque mapping, and pigment flow simulation. The Tree Oil Painting has previously been validated using X-ray imaging, FT-IR, XRF, and C-14 dating, confirming its 19th-century origin and natural pigment degradation profile.


Key Findings:

  • Over 10 out of 18 techniques scored above 90% similarity, including:
    • Sobel Edge: 96%
    • Pressure Map: 94%
    • Fourier Transform: 95%
    • LBP Texture: 95%
    • Brush Directionality: 93%
  • Strong rhythmic agreement in vertical torque strokes and directional flick vectors
  • Structural depth patterns in impasto mapping closely aligned after varnish correction
  • Scientific support from pigment and canvas dating reinforces forensic alignment

Strict Technical Advisory – AI Natural Matching Only

This dataset is to be used exclusively with AI Natural Matching systems that analyze:

  • Gesture torque
  • Directional stroke rhythm
  • Brushstroke layering and pressure mechanics

❌ SSIM (Structural Similarity Index Measurement) and pixel-based visual comparators are strictly prohibited.
They are not capable of detecting neural brushstroke signatures and will produce misleading results.

These images and metrics are designed to be interpreted through neural vector engines, deep-learning comparison models, and physical gesture recognition—not shallow similarity scores.


Created by: HaruthaiAI
Date: May 2025
Purpose: To provide an open, verifiable AI benchmark linking The Tree Oil Painting to Vincent van Gogh’s late-period techniques via gesture-level brushstroke analysis.

Let future AI and researchers test the evidence — and let art speak through motion, not just appearance.

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