EFFICIENT IMAGE RETRIEVAL USING COLOR AND TEXTURE FEATURES

Abstract

The CBIR approach is used to extract a picture from a big database. The color, texture, and form of an image are its most important components. The suggested method effectively extracts images by removing their attributes. Dominant color features allow predominant colors to be extracted to help with picture indexing. The Gray Level Co-occurrence Matrix (GLCM) is one method for characterizing the texture of images. Texture and color are not characteristics that set one apart. Shape information can be seen in edge images produced with gradient vector flow fields. Combining shape, texture, and color information results in a comprehensive set of attributes for image retrieval. The weighted Euclidean distance of shape, texture, and color can be used to distinguish between different kinds of photos. This retrieval approach uses a support vector machine to determine the significance of an image. This method will display images that are fairly similar to the one you requested.