Visual Retrieval Based on Combination of Histograms of AC Block Patterns and Block Neighborhood

Block transforms are currently widely used in various image and multimedia data. In addition, pattern recognition issues based on multimedia is a hot research area. In this paper, we proposed a new solution for pattern recognition problems, which is based on block transform. The idea is illustrated by an example of face retrieval application. The face images contain both the statistical and structural information, which representing the most important visual information. In this paper we use quantized block transform to represent this information in a compact manner. The problem is how to represent the statistical and structural information efficiently. The paper indicates a step in this direction by combining quantized block patterns and patterns neighborhood histograms. The results are illustrated by experiments using a public FERET database with good retrieval performance.