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This study focuses on the development of algorithm to reconstruct surface of a human head using Beta-Spline technique. The development of algorithm started with the data point extraction from CT scan images to parallel computation. Parallel computation is used to handle with the large number of data points. Ars Cluster, which is a low-cost parallel laboratory in UiTM Shah Alam, is used in this computation...
Accuracy is one of the most important requirements of a reconstructed surface. However, this criterion needs high computation too since large number of data points is involved. Therefore, distribution of data points is the best way to solve this problem. In this paper, dyadic rational technique is employed in segmenting the data points into several processors. Then, the surface reconstruction process...
This paper focuses on multi-slice image reconstruction for CT images using Beta-spline. In reconstructing multi-slice images especially from living image, issues like continuity and accuracy contours arise. Commonly, high continuity is hard to be achieved because of the accuracy requirement and vice versa. Thus the image reconstruction process is prolonged to fulfill these constraints. This paper...
Human head is one of the most detail parts of human body. Reconstruction of human head must be precise to avoid misinformation of the product. Furthermore, head reconstruction especially face is used in several significant applications such as face recognition, head surgery, and face simulation. This study employs cubic Beta-spline as the fitted curve based on its capability to maintain the second...
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