Patch-Based Oil Painting Forgery Detection Based on Brushstroke Analysis Using Generative Adversarial Networks and Depth Visualization

Patch-Based Oil Painting Forgery Detection Based on Brushstroke Analysis Using Generative Adversarial Networks and Depth Visualization

Art authentication has traditionally required deep expertise and knowledge of an artist’s work. Recently, computer vision algorithms have shown promise in image processing tasks; however, creating an automated model for painting authentication remains a challenge in art preservation and history. The...

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Bibliographic Details
Main Authors: Elhamsadat Azimi, Amirsaman Ashtari, Jaehong Ahn
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
patch-level oil painting’s forgery detection
conditional Generative Adversarial Networks
frequency analysis
depth information visualization
Reflectance Transformation Imaging
Online Access:https://www.mdpi.com/2076-3417/15/1/75
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