针对受自然光照影响的手形图像难以准确提取手形轮廓的问题，本文基于手形边界像素在垂直于边界方向上存在灰度突变的特性，提出了一种基于方向梯度极值的手形轮廓跟踪算法。该算法首先找到手形轮廓的起始点，然后按照一定的搜索方向和规则，在局部区域内计算候选点集中梯度极大值所在的点，并逐点跟踪极大值点，得到手形轮廓。将该方法在实验室自采图库及香港科技大学(HKUST)的手形图像库两个数据库中进行轮廓跟踪实验，结果显示，自采图库的跟踪准确率为100%，香港科技大学手形图像库的跟踪准确率为85.8%，该库中符合本文算法限制条件的图像的跟踪准确率为99.4%。实验结果表明，该方法能在灰度图像上直接跟踪出准确、连续、完整的手形轮廓，尤其适合于受光照不均影响的手形图像的边缘提取。

Hand contours are hard to be extracted correctly when hand images are illuminated by a unsymmetrical light.Therefore,this paper proposes a contour tracking algorithm based on the directional maximal gradient value according to the characteristic that values of edge pixels turn sharply in the vertical direction of an edge. The algorithm firstly finds the starting point of hand contour, then depending on some searching rules, it calculates the gradient values of candidate points in a local region, chooses the point whose gradient value is maximal in the candidate set of local region and tracks it point by point to get the final contour. Tracking experiments are carried out on both the hand image database formed by ourselves and the HandImage database from Hong Kong University of Science and Technology(HKUST) .Experimental results indicate that the accuracy of contour tracking is 100% in ourselves’ database,and 85.8% in the database from HKUST.Moreover,the accuracy of contour tracking in the images eligible to our refined condition from HKUST database is 99.4%. These data show that the algorithm can directly track out the accurate, consecutive and integral hand contour in gray-level picture and it is suitable especially for the contour extraction of hand images affected by the unsymmetrical illumination.