Tooth segmentation plays an important role in computer-aided orthodontics. However, many published approaches directly separate teeth from dental mesh without dealing with the region fusion, which leads to inaccurate results and incomplete segmented teeth with side shape lacked. Meanwhile, existing tooth shape modeling schemes are interaction-intensive and inefficient. To resolve this problem, a new tooth segmentation approach based on segmentation of feature line was proposed. Feature region was selected according to mean curvature, and morphologic algorithm was used to extract dentition line. The fusion region was automatically recognized by the feature line segmenting and branch points matching algorithm as well as morphologic dilation. The restoration result was automatically obtained by repairing holes with matched branch points. After the gingival margin lines between adjacent teeth were extracted, the teeth were segmented by all the gingival margin lines. Experimental results demonstrate that the poposed approach is accurate, the segmented teeth have complete side feature. In addition, the approach avoids user interactions in the stage of tooth shape modeling, thus improving the whole efficience by 60%-90% compared with the method which manually identifies and removes the interdental adhesion area and reconstructs the missing tooth surface by surface energy constraint.

The UMHexagonS motion estimation algorithm in H.264 was studied, and an improved fast motion estimation algorithm was proposed. First, the fixed search range, the unsymmetrical cross search, the 5×5 small rectangular spiral search, the uneven multi-hexagon-grid search and the extended hexagon-based search were analyzed. Then the optimized search modes were given respectively, which called dynamic search window, adaptive rood pattern search, the directional 3×3 small rectangular search pattern, the predictive intensive direction search and the modified extended hexagon-based search. Thus Adaptive Pattern Direction Search (APDS) algorithm was formed by these optimized search modes. The experimental results conducted on different test sequences show that, compared to UMHexagonS algorithm, the APDS algorithm can save about 29.64% Motion Estimation (ME) time and reduce the average number of checking points per Motion Vector (MV) generation about 21.64, while incurring nothing obvious loss in the reconstructed picture quality and less increment in the bit rate. With the efficiency improvement of ME, the real-time performance of the encoder is further enhanced.