An Optimized Digital Image Processing Algorithm for Digital Oil Painting

• Published in: Mobile information systems Vol. 2022; pp. 1 - 10
• Main Author: Tang, Jinyu
• Format: Journal Article
• Language: English
• Published: Amsterdam Hindawi 31.05.2022; Hindawi Limited
• Subjects: Algorithms; Computer networks; Decomposition; Digital imaging; Edge detection; Genetic algorithms; Image enhancement; Image processing; Image quality; Image segmentation; Information technology; Methods; Object recognition; Oil painting; Run time (computers); Skills; Software; Visual effects
• ISSN: 1574-017X; 1875-905X
• DOI: 10.1155/2022/4956839

Human civilization’s accomplishments have grown with the passage of time and the advancement of society. With the fast growth of computer networks and information technology, the conventional method of information transmission based on words cannot fulfill the demands of people in the current era. As a result, in this age of extensive information and image processing techniques, images as a means of information sharing are becoming increasingly popular. As we know, digital image processing knowledge has a far-reaching impact in the field of artistic creation, among which the creation of oil painting is facing severe challenges. Aiming at the problem that the effect of digital oil painting is not ideal, this paper aims to study digital oil painting by using digital image processing technology. This paper first uses the image edge recognition based on the improved Canny algorithm to detect the edge of the oil painting image, then uses the nonlinear image enhancement algorithm to enhance the effect of the oil painting image, then uses the improved genetic algorithm to segment the image, and finally enlarges the oil painting image to calibrate the color of the oil painting image. Experiments reveal that the proposed approach outperforms existing algorithms in terms of edge detection data integrity, high-quality coefficient index of image enhancement, picture segmentation running time, and the ability to successfully increase the visual effect of oil painting.