Digital Media Image Recognition Method Based on Improved Fuzzy C-means Clustering Analysis

Abstract

Digital media plays a more and more important role in people’s life. In recent years, as an important part of digital media, image is widely used. It has become a hot spot in image information processing to determine the similarity between images by calculating the perceptual hash. This paper mainly studies the intelligent traceability of digital image based on improved fuzzy c-means clustering analysis. This method can improve the information truth degree identification of data image, which can assist the development of data image information detection and recognition system based on improved fuzzy c-means clustering analysis. Firstly, this paper analyzes the value of image recognition technology in streaming media environment. For the current streaming media image recognition technology, the main application areas and demand state are described. Then, from the perspective of technology, several main technologies in this field are discussed, and the digital image technology of improving fuzzy c-means clustering analysis is analyzed and constructed. Experimental results show that the method can improve the efficiency and accuracy of digital media image recognition. This method has a certain reference value to promote the development of digital image analysis technology.