目标形状表达算法综述

Review of Shape Representation for Objects

形状的检索和识别在医疗诊断、目标识别、图像检索和计算机视觉等领域都有重要应用,而高效的形状检索和识别取决于形状表达算法的优劣.给出了形状表达优劣的一般判断标准,对目前的主要形状表达方法进行分类,包括线性组合表达、空间关联关系表达、基于微分和积分的特征表达,以及变形表达等方法.对每一类方法,从使用的数学模型、多分辨率表达能力、不变量、鲁棒性、形状重构、信号噪声分辨性能等方面进行分析和综合评价,指出这些表达方法的优劣,尤其是就这些算法的数学机理进行分析探讨,并给出了未来需要进一步研究的方向和思路.

Shape retrieve and objection are widely applied into medical diagnostics,target recognition,image retrieve and computer vision,etc.The efficient retrieve and objection of shapes completely depend on an excellent shape representation algorithm.This paper proposed the assessment criterion for shape representation.Then,according to the criterion,the existing shape representations were categorized into linear combination representations,spatial association relationship,feature representation based on differential and integral property of shapes and deformation representations.Each of these methods was analyzed and accessed in terms of mathematical principle,the ability of multiscale representation,variants,robust,reconstruction of original shapes,identification of signal and noise,etc.Furthermore,the advantages and disadvantages of each algorithm were discussed,especially,explored from the principle of mathematics.Finally,the suggestions for the future research were also given.