Facial expression is one way humans convey their emotional states. Accurate recognition of facial expressions via image analysis plays a vital role in perceptual human computer interaction, robotics and online games. This paper focuses on recognising the smiling from the neutral facial expression. We propose a face alignment method to address the localisation error in existing face detection methods. In this paper, smiling and neutral facial expression are differentiated using a novel neural architecture that combines fixed and adaptive non-linear 2-D filters. The fixed filters are used to extract primitive features, whereas the adaptive filters are trained to extract more complex features for facial expression classification. The proposed approach is evaluated on the JAFFE database and it correctly aligns and crops all images, which is better than several existing methods evaluated on the same database. Our system achieves a classification rate of 99.0% for smiling versus neutral expressions.