Content-Based Image Retrieval Using Zernike Moments for Binary and Grayscale Images

Image features play a vital role in image retrieval. This chapter presents the use of Zernike moment features for retrieving the binary and gray level images from established image databases. To retrieve a set of similar category of images from an image database, up to 25 Zernike moment features from order zero to order 8 were utilized and experimented in this chapter. A total of 1400 binary images from MPEG-7 dataset and 1440 images from a COIL-20 dataset were used to evaluate the capability of Zernike moments features for image retrieval. The experimental results show that Zernike moments implementation is suitable for image retrieval due to rotation invariance and fast computation.