复杂物体轮廓提取

图象分割是图象处理中的一项重要工作，虽然目前手工与自然相结合的分割方法已在实际工程中得到了广泛应用，但由于图象的多义性和复杂性，许多分割工作仍无法利用计算机来自动完成，为了解决这一问题，根据图象经Maar变换后的特征，采用新的判断准则，提出了一种复杂物 体边缘定位算法，用该算法 具有尖角特征的特体轮廓进行快速准确地提取，同时由于利用了矢量化方法来消除毛刺，从而使跟踪获得的边界更符合物体的实际轮廓特征，通过对多种图象的实验表明，该方法十分有效。

Extraction of Complex Object Contour

Image segment plays an important role in the field of image processing, and currently the hybrid approach combining the manual and automatic methods is widely used in segment practice. In this paper we present an algorithm capable of locating the target object contour of sharp tips accurately in the interactive rate. Considering that the edge are usually on the zero-crossing points after Marr transformation for most images, existing techniques tend to give undesirable results because the energy path containing more points is given less priority. In our method we specify a pointer to point the current point on a path of interest, when the energy of current path is less than the energy for the previous point, we checknlatest points in the current path instead of checking only one point as existing techniques do, and, if more thanmpoint (m n) is zero-crossing, the pointer of the point is updated, otherwise, the pointer remains unchanged. Using this criterion we can insert new seeds automatically near the tips of the target object and the burr is eliminated by a vectorization approach. The final contour traced out fits the feature of the target object well and the effectiveness of our method is demonstrated by examples shown in the paper.