A Survey on Content Based Image Retrieval Using Color, Texture and Shape Features

Vivek Verma; Punit Kumar Johari

doi:10.37591/joosdt.v2i2.464

Abstract

Due to increase in volume of images in database, content based image retrieval becomes a challenging problem. To overcome such problems and efficient access of images from database, image retrieval uses low level features such as color, shape and texture that are prominent to retrieve the images. These features are extracted from the images. At last images are retrieved relevant to the query image from the database based on the similarity measurements. In this paper some low level features and their limitations are described. Furthermore, future scope is also suggested. Relevance feedback technique can be used to reduce the semantic gap between human perception and computerized system.Keywords: CBIR, color histogram, color moments, Tamura texture feature, Hu moments, Zernike moments Cite this ArticleVivek Verma, Punit Kumar Johari. A Survey on Content Based Image Retrieval Using Color, Texture and Shape Features. Journal of Operating Systems Development & Trends. 2015; 2(2): 1–8p.