Moments have been widely used for creating invariant features for image classification and object recognition problems. In this study, different moments that are extracted from a database of 1200 images are used for object classification. The images are obtained from 10 different objects, each of which had 120 images that are rotated in different angles with different lighting conditions. For performance analysis, geometric invariant moments, Zernike moments, Pseudo- Zernike moments, Tchebichef moments and statistical features of the objects are extracted from each image. 800 of the images (80 images from each object) were used in training and the remaining 400...