Moment based Object Classification from Shapes

A flexible object recognition system is considered which can compute the good features for high classification of objects. To characterize an output class or object usage of appropriate features is vital for all classification problems. Moment invariant functions are very useful for object classification, regardless of its orientation, size and position. The main features leading us to our objective are representations of objects using 2D images. The proposed paper focus on, the classification performance of classifiers with moment–based feature sets is introduced after only efficient feature extraction. The experimental results shows that the proposed feature descriptor performs well with existing texture descriptors in terms of classification accuracy