This paper presents a dynamic programming algorithm for identification and labeling for intrinsic and extrinsic factors of face appearance. The novelty of the proposed technique is based on a new combination of mapping network, called wavenet-network (WN) and Inverse Discrete Multi-Wavelet Transform (IDMW). Wavenet is induced by combining the wavelet transform model with the basic concept of neural networks. The new mapping network called wavenets is proposed as an alternative method to feed forward neural networks to approximate the arbitrary nonlinear functions. Wavenet (WN) was employed to make approximation to the images before passing through the Inverse Discrete Multi-Wavelet Transform (IDMW) decomposition to extract image descriptive features. These features are used in neural networks of the proposed image identification algorithm to define the test image. A successful identification rate of: 99% was achieved with this approach for the intrinsic factors and 93% was achieved with this approach for the extrinsic factors. The algorithm is implemented using MATLAB programming languages version 7.