Subdivision surface is a refinement method applied to the entire polygon mesh in order to produce a smooth surface in any 3D object. This method has issues in terms of time and memory consumption due to the fact that it computes and renders all of the vertices of the mesh during the subdivision process. To overcome this issue, adaptive subdivision surface method is used because it would subdivide only at the required vertices of selected areas and decrease the number of polygons on the mesh. However, a related issue in the use of this method has risen,which is the determination of a suitable threshold value to be used for selecting the subdivision area. Besides that, the use of a higher level of subdivision will lead to an increase in the number of polygons and this would lead to heavy computational load and raise high undulation on the curve surface. To address these issues, Iterative Adaptive Subdivision Surface (IteAS) method is proposed. In this method, the area to be subdivided will be identified by using the threshold value. To get the optimal threshold value, a new formula based on statistical evaluation was embedded in the proposed method. Here, the threshold value is defined as the average value of a normal vector between the rates of 0° to 180° in a 3D object. The value will be compared with the angle between normal vectors, if the threshold value is greater than the angle, the surface will be subdivided by using Butterfly subdivision scheme. The results from this process will determine the number and levels of iteratives in the subdivision surface. The number of iteratives relieson the surface shape of the 3D object which is either a curve or flat surface. The number of iteratives will be higher for a flat surface as compared to a curve surface.In this research, IteAS can reduce 18% to 25% number of polygons as well as 1% to 3% use of computational memory whilst retaining the smoothness of the surface. This IteAS method has been proven to improve the present enhancement process.
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