Title: Feature perception based graphic advertising image generation technology

Authors: Huichao Zhang

Addresses: School of Design and Arts, Taiyuan University of Science and Technology, Taiyuan, 030024, China

Abstract: In order to meet the market demand for graphic advertising images, this article proposes a feature aware image generation technology for print advertising. This technology quantifies image features, uses simulated annealing algorithm to sample the quantised features, and then combines dictionary strategy to optimise probability models to predict feature distribution, ultimately generating the optimal graphic advertising image. The results show that in terms of iteration error rate, the simulated annealing algorithm tends to stabilise after 85 iterations, with an error rate of 0.015. In terms of colour feature extraction rates, the simulated annealing algorithm has extraction rates of 92%, 91.5%, and 89.1%, respectively. In expert evaluation, the expert evaluation scores all exceed 90 points. The above data indicates that the proposed method is feasible and can provide technical support for related advertising image generation.

Keywords: graphic advertising; image generation; simulated annealing algorithm; lexicographic strategy; feature perception.

DOI: 10.1504/IJCSYSE.2026.151334

International Journal of Computational Systems Engineering, 2026 Vol.10 No.1/2/3/4, pp.47 - 57

Received: 01 Aug 2023
Accepted: 05 Sep 2023
Published online: 26 Jan 2026 *

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