Neutrosophic Features for Image Retrieval
Keywords:Content-Based Image Retrieval (CBIR), Textbased Image Retrieval (TBIR), Neutrosophic Domain, Neutrosophic Entropy, Neutrosophic Contrast, Neutrosophic Energy, Neutrosophic Homogeneity
Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in  is a generalization of fuzzy sets which introduced by Zada at 1965 , The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].
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