Haar Wavelet Untuk Ekstraksi Fitur Energi, Standar Deviasi, Dan Histogram Dalam Sistem Temu Kembali Citra

Abstract

Image retrieval initially uses a query in the form of text to search for images in the database. Image search using text query has a weakness because of the limited description of information stored or given by humans to the metadata on an inconsistent image that greatly affects the duration of searching an image in a database. Content based image retrieval (CBIR) is an image processing application to find the image sought in a large image database based on a query or user request. CBIR technique utilizes features that exist in images, namely color, texture, and shape. These features will be used as a basis for searching images in an image database. In this study the authors used the Haar wavelet method and histogram to look for texture and color features in the image. Then the features found are matched with features stored in the database using the Euclidian distance method. In this study the authors used the Corel dataset as research material. The dataset used is classified into 3 categories: bus, animal and sunset. Each category consists of 100 images where 70% are training images and 30% are test images.