Analysis of Adaptive Morphology for Visualization of Information Communication in Advertising Design

Abstract

Abstract This paper uses adaptive morphology to construct an adaptive elliptic structure element that changes adaptively according to the image’s local neighborhood information. To calculate convolution, a Gaussian kernel with the outer product of the image gradient is used to achieve the diffusion of the linear matrix values of the initial matrix. The spatial distance of the pixels determines the size of the structural elements, and the pixel points that do not exceed the threshold are selected. The adaptive morphology method resulted in a 27.7 difficulty level for visual communication design, and the algorithm’s accuracy was 87.18%. Advertising design can break through dimensional limitations in visual space through adaptive morphology to generate interaction, indicating a path for development.