Similar Image Retrieval via Gray-Level Features
With the rapid development of multimedia technology and exponential growth of visual data, efficient management and retrieval of visual information resources have become increasingly crucial. Consequently, Content-Based Image and Video Retrieval (CBIR) techniques have gained significant attention as key research directions in multimedia information retrieval and image processing. CBIR technology provides robust support for managing and accessing large-scale image databases. This paper introduces a gray-level feature implementation method for content-based image retrieval, presenting both theoretical significance and practical application value. It investigates current research status, key technologies, technical bottlenecks, and development trends of CBIR. The co-occurrence matrix method statistically analyzes all image pixels to characterize gray-level distributions, with particular focus on generalized image gray-level co-occurrence matrix applications.