Analysis of Visual Communication Effect of Color in Print Advertising Design Based on Decision Tree Classification Algorithm

With the rapid development of modern computer network technology and image storage technology, the number of image data on the Internet has increased dramatically, and there is a phenomenon that image data is extremely rich, but useful image information and knowledge are poor. Therefore, there is an urgent need for a technology for mining useful information in image data, so image mining technology came into being. As an exciting and active branch of cognitive science and computer science, digital image processing technology has received great attention and made great progress in recent years. In particular, the rapid growth of visual information and the ever-increasing need for applications have caused the study of algorithms that can handle a variety of diverse domains and activities to become the primary focus of image processing and fields that are closely related to it. This study makes use of a classification approach known as decision trees, and the decision tree algorithm is the end product of a data classification scheme in which the tree structure plays a central role. The nodes of the tree that are not leaf nodes represent the test of the data characteristics; each branch of the tree represents an output of the test, and each leaf node indicates a classification. By specifying the path that starts at the root node and continues to each leaf node, one can obtain a variety of categorization criteria. According to the findings of the research presented in this article, the algorithm presented in this paper possesses outstanding effectiveness and is suited for widespread use.