高级检索
李宝顺, 贡文凯, 包亚萍, 李义丰. 基于最小二乘法的鼻子轮廓提取[J]. 计算机辅助设计与图形学学报, 2017, 29(5): 814-820.
引用本文: 李宝顺, 贡文凯, 包亚萍, 李义丰. 基于最小二乘法的鼻子轮廓提取[J]. 计算机辅助设计与图形学学报, 2017, 29(5): 814-820.
Li Baoshun, Gong Wenkai, Bao Yaping, Li Yifeng. Nose Contour Extraction Based on Least Square Method[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(5): 814-820.
Citation: Li Baoshun, Gong Wenkai, Bao Yaping, Li Yifeng. Nose Contour Extraction Based on Least Square Method[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(5): 814-820.

基于最小二乘法的鼻子轮廓提取

Nose Contour Extraction Based on Least Square Method

  • 摘要: 针对传统的机器人肖像绘画技术中,现有方法难以对提取的鼻子轮廓线条的特征进行表征,进而影响了对鼻子的编码和矢量化的问题,提出一种基于最小二乘法的鼻子轮廓提取算法.首先在检测鼻子的基础上定位鼻尖和鼻孔;然后定位关键特征点,并通过关键特征点的约束控制搜索轮廓参考点;最后基于最小二乘法拟合轮廓曲线,得到鼻子轮廓曲线.实验结果表明,应用该算法能很有效地提取鼻子轮廓特征,且有利于编码和矢量化.

     

    Abstract: It is hard for the traditional robotic portraying technology to represent the extracted nose contour, thus influencing the encoding and vectorization for the nose. Hence, a nose contour extraction algorithm has been presented based on the least square method. Firstly, the nose tip and nostrils are positioned after the nose has been detected. Then the key feature points are positioned, and the contour reference points are searched by constraining and controlling the key feature points. At last, the nose contour curve is fit based on the least square method, thus obtaining the nose contour curve. Experiments show that our method can effectively extract the features of nose contour and also facilitate the encoding and vectorization.

     

/

返回文章
返回