Title: Study on colour distortion correction method of two-dimensional art image based on naive Bayes

Authors: Quan Gan; Yucai Zhou

Addresses: Department of Architecture, Henan Technical College of Construction, Henan 450064, China ' School of Energy and Power, Changsha University of Science and Technology, Changsha 410076, China

Abstract: Aiming at the problems of low correction accuracy and long correction time in the traditional two-dimensional art image colour distortion correction method, a two-dimensional art image colour distortion correction method based on naive Bayes is proposed. Through the RGB image sensor, the brightness pixels are relatively evenly distributed on the histogram through the conversion of four links: world coordinate system, camera coordinate system, photosensitive device coordinate system and pixel coordinate system. Binarisation is carried out based on naive Bayes. According to the binarisation results, the salient regions of two-dimensional art images are extracted. Based on the obtained key regions, the multi-scale retinal algorithm with colour restoration is used to correct the colour distortion of two-dimensional art images. The experimental results show that the proposed method has the highest accuracy and the shortest correction time.

Keywords: naive Bayes; 2D art image; colour distortion; histogram equalisation; multi-scale retinal algorithm.

DOI: 10.1504/IJRIS.2023.136368

International Journal of Reasoning-based Intelligent Systems, 2023 Vol.15 No.3/4, pp.297 - 303

Received: 09 Jun 2022
Accepted: 27 Oct 2022
Published online: 31 Jan 2024 *

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