Optimization CBIR using K-Means Clustering for Image Database
Juli Rejito, Retantyo Wardoyo, Sri T. Hartati, Agus Harjoko · 2012
The CBIR (Content Based Image Retrieval) implementation in searching images into image database requires usually for a sufficiently prolonged time because such image searching process is performed with comparison between searched images and individually records in an image database. In this work, it is proposed a K-Means clustering algorithm aiming to develop clusters from each image database records, it can later be used for optimizing image searching access period. The stored images in image database records are only limited for the JPEG-type images. In this algorithm, cluster formation is based on maximum and minimum PSRN's (Peak Signal to Noise Ratio) calculation values from individual records on a basic images and it will be treated as key images in every search for records with such cluster utilization. Results of the clustering process in form of cluster table would be made as indexing in early image searching for cluster position determination from searched images to image records.