Classification and recognition of objects is interest of many researchers. Shape is a significant feature of objects and it plays a crucial role in image classification and recognition. The present paper assumes that the features that drastically affect the adulthood classification system are the Shape features (SF) of face. Based on this, the present paper proposes a new technique of adulthood classification by extracting feature parameters of face on Integrated Texton based LBP (IT-LBP) images. The present paper evaluates LBP features on facial images. On LBP Texton Images complex shape features are evaluated on facial images for a precise age classification.LBP is a local texture operator with low computational complexity and low sensitivity to changes in illumination. Textons are considered as texture shape primitives which are located with certain placement rules. The proposed shape features represent emergent patterns showing a common property all over the image. The experimental evidence on FGnet aging database clearly indicates the significance and accuracy of the proposed classification method over the other existing methods.