BIP: A dimensionality reduction for image indexing

Abstract

Searching on internet is one of the daily task done by millions of users around the Globe. There is an urge for effective indexing scheme for unstructured data, which provide better search results. The image, content report, and site pages are said to be unstructured database. These information are not sorted out so the recovery rates of these information are purposely low when contrasted with indexed database. These information are indexed concerning their cues is one of the challenging areas to be explored. For the client require, the data recovery segment endeavors to coordinate the client question with the indexed database will provide effective recovery rates. In this paper a new image indexing scheme called Basic intrinsic pattern (BIP) is elaborated, which uses the image intensity as the key variable for image indexing. The algorithm is evaluated with respect to the size of the feature vector and the retrieval rate. Keywords: Image indexing, Gradient, GLCM, PCA, Texture