Artwork’s Authenticity Recognition Model Using Machine Vision and Applications

Abstract

Majid Mirbod

This paper presents an artwork authenticity recognition model using machine vision, image processing, and a fuzzy interface system and it is an applied research category. Artworks have always been subject to copying due to their importance, uniqueness, and great financial value, and it has always been the focus of international counterfeiters worldwide. Throughout history, due to various incidents, artworks have been stolen, crossed the borders of different countries, and traded in various auctions. Therefore, recognizing and confirming an artwork's authenticity is always challenging. In this research, I try to present a model to verify the authenticity of artwork using artificial intelligence techniques. The basic assumption is that a quality image of the original artwork is available with the specifications that I will explain in the section. Indeed, two images will be compared by taking pictures of other samples, and their differences will be identified with high accuracy, which the human eye cannot recognize. So, this model cannot recognize artwork authenticity without imaging history. In other words, photographing the original artwork can be used as a basis for comparison with other fake copies of it in the future, and by using the proposed model, their authenticity can and will always be checked. This model is based on my previous research on micrographics imaging to Industrial parts change recognition, the details of which will be explained in the text of the article. In this research, seven unique and famous world artworks were used and two samples of their images were compared to the original sample. The validity and reliability of the results and the high accuracy were obtained with one pixel.

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