Content-Based Image Retrieval System using Color Moment and Bag of Visual Words with Local Binary Pattern

Researchers have recently focused their attention on Content-Based Image Retrieval (CBIR). It has emerged as one of the most fascinating areas in image processing and computer vision. With CBIR, comparable pictures that match query are pulled from an database. As a result, it necessitates feature extraction (Local / Global) similarity calculation. This paper uses CBIR technique to determine images best by utilizing both global local features. A color moment is used for features describe complete image. Local Binary Pattern (LBP) feature, other hand, extracts interest points building Bag Visual Words (BoVW). The distance between database computed using Euclidean distance. Precision recall Corel-1K dataset assess retrieval performance.