Conceptional review of the Content-based Image retrieval

This article examines the process of the Content-based Image Retrieval (CBIR ) system , the features and steps involved, the methods employed, and the applications. CBIR aims to identify, sort, and manage images on the basis of the requirements posed to the system. The system cross checks the requirements using Machine learning processes against a given database and reduces the manual effort of sifting through all pictures individually.
Incorporating references to the different methods of feature extraction, this article emphasizes understanding which features are considered important and the characteristics of features that are searched for. It argues the advantages of multiple methods while suggesting how each method is suitable when employed for a specific purpose. The process of indexing is also highlighted in this article. These processes are particularly useful in this advancing world where huge databases of images need to be handled on a daily basis in various applications and where manual methods are simply not feasible.