摘要
提出一种新的复杂场景下的目标图像提取方法。给出一种改进的Snake模型,并将其应用到初始模板的建立中;引入分形布朗随机场模型,利用小波分形维数和分形拟合误差确定可能的目标区域;定义了一种新的最小失配距离(MMD)相似性度量,并基于目标的特征区域进行快速相关匹配。该算法通过精确建立初始模板和采用由粗到精的目标搜索策略,既保证了目标提取的精度,又大大减少了计算量。
A new target extracting algorithm for complex scene is proposed. An improved Snake model is presented and applied to the construction of initial template, and the fractal Brown random field model is introduced to work out the possible target region according to the wavelet fractal dimension and fractal fitting error. After that, a new minimurfi mismatch distance （MMD） similarity measurement is defined, and the correlation matching is made quickly based on the feature region of the target. By accurately constructing initial template and using coarse- to-precise target searching strategy, the algorithm guarantees good extraction precision and reduces the computation greatly.
出处
《应用光学》
CAS
CSCD
2008年第6期837-843,共7页
Journal of Applied Optics
基金
国家自然科学基金资助项目(10376043(A06))
