An object recognition procedure using artificial neutral network is proposed in this paper. This algorithm will recognize objects in the images which are invariant to rotation, translation and scaling of objects. The Sobel operators are proposed to detect the boundary of the object. A Fourier descriptor pattern classifier is able to classify object without regard to rotation, translation and scale variation. Fourier descriptors of boundary image generate Feature vectors by truncation the high frequency components. A back-propagation neural network is proposed to recognize the object based on these Feature vectors.