A Survey: Content Based Image Retrieval Based On Color, Texture, Shape & Neuro Fuzzy

In current technology the acquisition, transmission, storing, and manipulation are allowed on the large collections of images. With the increase in popularity of the network and development of multimedia technologies, users are not satisfied with the traditional information retrieval techniques. So nowadays, the content based image retrieval is becoming a source of exact and fast retrieval. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc. to search user required image from large image database according to user's requests in the form of a query image. Images are retrieved on the basis of similarity in features where features of the query specification are compared with features from the image database to determine which images match similarly with given features. Feature extraction is a crucial part for any of such retrieval systems. So far, the only way of searching these collections was based on keyword indexing, or simply by browsing. Literature survey is most important for understanding and gaining much more knowledge about specific area of a subject. In this paper we survey some technical aspects of current content-based image retrieval systems and described the image segmentation in image processing and the features like neuro fuzzy technique, color histogram, texture, and shape for accurate and effective Content Based Image Retrieval System after doing the deep study of related works. Keywords— Content-Based Image Retrieval (CBIR), Neuro Fuzzy, Color Histogram, Texture, HSV Color and Wavelet decomposition, Image Segmentation.