摘要： 针对一般梯度矢量流(GVF)分割对连续对象分割效果差、迭代次数较多的缺点，提出一种基于GVF的运动目标提取模型。该模型计算运动目标的大致范围(以矩形框架表示)，并利用该矩形框架的限制进行初始化处理，得到初始化轮廓，使用改进的GVF算法提取出对象。对运动目标序列的实验结果表明，该方法可以较大地提高计算速度。
关键词:
图像分割,
梯度矢量流,
轮廓,
矩形,
GVF蛇形,
运动目标
Abstract: Aiming at the shortage of Gradient Vector Flow(GVF), a new moving object extraction algorithm based on improved GVF is proposed. A rectangle limiting the range of target is established by experience and displacement equation. Initial contour according to rectangle range is obtained by rules. The algorithm of GVF is improved, which is used to calculate fine contour. Experimental results in sequence display the algorithm is simple and rapid.
Key words:
image segmentation,
Gradient Vector Flow(GVF),
contour,
rectangle,
GVF snake,
moving object
中图分类号:
徐俊红, 丁春峰, 苏海滨, 王亭岭. 基于改进GVF的运动目标提取算法[J]. 计算机工程, 2012, 38(9): 199-201.
XU Dun-Gong, DING Chun-Feng, SU Hai-Bin, WANG Ting-Ling. Moving Object Extraction Algorithm Based on Improved GVF[J]. Computer Engineering, 2012, 38(9): 199-201.