Design Approach for Content-Based Image Retrieval Using Gabor-Zernike Features

Features from an image is known as Content-based Image Retrieval. Color, Texture and Shape are the major features of an image and play a vital role in the representation of an image..In this paper, a novel method is proposed to extract the region of interest(ROI) from an image,prior to extraction of salient features of an image.The image is subjected to normalization so that the noise components due t The process of extraction of different o Gaussian or other types of noises which are present in the image are eliminated and the successful extraction of various features of an image can be accomplished. Gabor Filters are used to extract the texture feature from an image whereas Zernike Moments can be used to extract the shape feature.The combination of Gabor feature and Zernike feature can be combined to extract Gabor-Zernike Features from an image.