Application of graphic image processing technology in 2D game interface design

This paper uses big data information processing techniques for the underlying algorithm of interface interaction, calculates the number of game interface data points, and satisfies the hierarchical feature distribution of interface interaction. Using cross-compilation for information clustering, identifying fuzzy clustering central function feature classification, describing the underlying data statistical independent variables, and extracting graphical local feature information. Balancing constraint encoding and dictionary coefficient weighting parameters, processing edge feature images, and matching grayscale transformed image effects are conveyed. The results show that the image graphics technology has an accuracy rate of 87.25% for image recognition, the user satisfaction rate for the 2D game design interface is 78.60%, and users aged 30-40 are the largest group of game consumers. It indicates that graphic image processing technology can collect and obtain relevant information and data, thus providing important technical support for the development of the social game industry and promoting the deepening development of an information society.