Expression of Concern: Oil painting color image enhancement recognition method based on artificial intelligence: applications of an AI model in environmental research

Abstract

ABSTRACT Due to the pollution of the air and water environment and the problem of forgery, it is difficult to identify oil paintings. The reason is that air pollution and water pollution can lead to moisture, mold, and even water stains on the picture, which will seriously damage the integrity and color performance of the picture. At the same time, chemicals in the water may also have a corrosive effect on the oil painting, further destroying the color and detail of the picture. The problem of relying entirely on the conventional experience of experts is too subjective. Some controversial works are difficult to convince people with rational identification evidence, so it is necessary to explore a scientific and effective method to quantify the authenticity of oil paintings. This paper constructs an oil painting authenticity identification method based on multi-feature fusion based on the artistic style analysis and feature extraction of oil painting shape, color and texture. The recognition accuracy of the proposed method is compared with that of the existing neural network. The results show that the recognition rate of the proposed model is 73.0%, which is the best performance.