共查询到19条相似文献,搜索用时 203 毫秒
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基于确定性退火技术的鲁棒性的点匹配算法 总被引:6,自引:0,他引:6
点匹配问题一直是计算机视觉和模式识别领域的一项重要的基础性工作,该文提出了一种基于确定性退火技术的准确,快速和鲁棒性的点匹配方法,该方法首先确定在一一对应双向约束的点匹配问题的自由能函数,通过最小化该能量函数可以同时得到点集之间的匹配矩阵和映射参数,由于将匹配矩阵的估计嵌入到确定性退火算法的框架下,利用退火温度来控制匹配矩阵的模糊度,不仅增强了算法的鲁棒性,而且减小了陷入局部极小的可能性,另外,在该算法中通过引入松驰变量,可以鲁棒性地处理出格点(outliers),实验结果验证了该算法的有效性和鲁棒性。 相似文献
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针对合成孔径雷达(SAR)图象自动目标识别问题,在对SAR图象的特征提取问题进行分析的基础上,提出了一种特征点匹配算法,该算法根据Birkhoff-von Neumann定量,首先将广义置换矩阵约束松驰为广义双随机矩阵约束;然后利用拉格朗日乘子和障碍函数法,把约束加到目标函数中,从而将点集匹配问题转化为非线性最优化问题;最后利用确定性退火和软分配技术求解该问题,将得到的匹配代价用特征点数目的比值进行修正后,用于目标的识别。实验结果表明,该算法非常有效。 相似文献
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一种采用二次式作为阻尼项的点匹配算法 总被引:1,自引:1,他引:1
为了对基于确定性退火技术的点匹配算法进行改进,提出了一种采用二次式作为阻尼项的算法。现有的此类算法为了控制匹配矩阵P的熵,通常都在目标函数中加入∑Pi,jlogpi,j形式的阻尼项,其缺点是需要用迭代逼近的方法使P满足双向的行列约束,由于这会因引起误差的积累而降低算法的整体匹配精度,为此,提出采用∑Pi,j(Pi,j-1)形式的阻尼项,这样目标函数就成为P的正定二次式,因而就可以在退火的每一步求解出使目标函数最小的Po仿真结果表明,该新算法在精确性和稳定性方面都有显著的改善。 相似文献
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在图像角点匹配过程中,目标图像往往存在平移旋转现象,直接影响匹配效果,为此提出了一种平移旋转图像的角点匹配方法。该方法首先利用角点检测生成自相关矩阵的梯度信息与仿射变换相结合,构造确定性退火算法中的自由能函数,然后对该自由能函数进行优化,获取待匹配角点间的仿射变换参数,最后利用该变换参数实现角点匹配。实验结果表明,该方法能够在目标图像发生平移旋转的情况下,有效实现角点匹配。 相似文献
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基于最大熵和互信息最大化的特征点配准算法 总被引:18,自引:0,他引:18
点配准问题在机器视觉、医学图像等领域,有着非常重要的应用基础.通过在最大化熵原理的基础上,将互信息相似性测度引入到点配准算法中,提出了一种新的快速、准确的健壮性的点配准算法.首先建立起表示两个特征点集之间匹配对应关系的联合概率分布匹配矩阵,通过最大化熵和互信息最大化,建立起一个包含匹配矩阵和空间变换参数的新的能量函数,通过确定性退火算法,可以获得最优的匹配矩阵和空间变换参数,从而解决点的对应性问题和出界点(outliers)确定.实验结果表明,算法具有较强的鲁棒性,具有较高的配准精度和较快的计算速度. 相似文献
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针对"平行视"多视视频,提出了一种基于非标定摄像机仿射变换的块匹配算法.该算法采用Harris算子提取角点,依据特征跟踪法和线段仿射性质作为同名点匹配准则,利用同名点信息构造摄像机仿射变换矩阵,在此基础上实现视问块匹配.实验结果表明,该算法可有效提高"平行视"块匹配效果. 相似文献
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为了能对等距变换和相似变换后的图像进行精确匹配,提出了一种基于图的Laplace谱的特征匹配方法,该方法是首先给定两幅图像的特征点,然后分别定义其Laplace矩阵,再通过分析该矩阵的特征值及特征向量来构造特征点匹配矩阵;最后根据匹配矩阵元素的大小和位置信息来实现特征点匹配,并从理论上证明了该算法在对图像进行等距变换或相似变换情况下能获得精确匹配。实验结果表明,该方法对真实图像的匹配精度可达到82%。 相似文献
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We present an algorithm for matching two sets of line segments in 3D that have undergone non-rigid deformations. This problem is motivated by a biology application that seeks a correspondence between the alpha-helices from two proteins, so that matching helices have similar lengths and these can be aligned by some low-distortion deformation. While matching between two feature sets have been extensively studied, particularly for point features, matching line segments has received little attention so far. As typical in point-matching methods, we formulate a graph matching problem and solve it using continuous relaxation. We make two technical contributions. First, we propose a graph construction for undirected line segments such that the optimal matching between two graphs represents an as-rigid-as-possible deformation between the two sets of segments. Second, we propose a novel heuristic for discretizing the continuous solution in graph matching. Our heuristic can be applied to matching problems (such as ours) that are not amenable to certain heuristics, and it produces better solutions than those applicable heuristics. Our method is compared with a state-of-art method motivated by the same biological application and demonstrates improved accuracy. 相似文献
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A new point matching algorithm for non-rigid registration 总被引:9,自引:0,他引:9
Feature-based methods for non-rigid registration frequently encounter the correspondence problem. Regardless of whether points, lines, curves or surface parameterizations are used, feature-based non-rigid matching requires us to automatically solve for correspondences between two sets of features. In addition, there could be many features in either set that have no counterparts in the other. This outlier rejection problem further complicates an already difficult correspondence problem. We formulate feature-based non-rigid registration as a non-rigid point matching problem. After a careful review of the problem and an in-depth examination of two types of methods previously designed for rigid robust point matching (RPM), we propose a new general framework for non-rigid point matching. We consider it a general framework because it does not depend on any particular form of spatial mapping. We have also developed an algorithm—the TPS–RPM algorithm—with the thin-plate spline (TPS) as the parameterization of the non-rigid spatial mapping and the softassign for the correspondence. The performance of the TPS–RPM algorithm is demonstrated and validated in a series of carefully designed synthetic experiments. In each of these experiments, an empirical comparison with the popular iterated closest point (ICP) algorithm is also provided. Finally, we apply the algorithm to the problem of non-rigid registration of cortical anatomical structures which is required in brain mapping. While these results are somewhat preliminary, they clearly demonstrate the applicability of our approach to real world tasks involving feature-based non-rigid registration. 相似文献
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一种基于退火策略的混沌神经网络优化算法 总被引:41,自引:0,他引:41
Hopfield网络(HNN)中引入混沌机制,首先在混沌动态下粗搜索,并利用退火策略控制混沌动态退出和逆分贫出现,进而HNN梯度优化搜索,提出了一种具有随机性和确定性并存的优化算法,对经典旅行商(TSP)的研究,表明算法具有很强的克服陷入局部极小能力,较大程度提高了优化、时间和对初值的鲁棒性能,同时给出了模型参数对性能影响的一些结论。 相似文献
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一种混沌Hopfield网络及其在优化计算中的应用 总被引:2,自引:0,他引:2
文章讨论了神经网络算法在约束优化问题中的应用,提出了一种混沌神经网络模型。在Hopfield网络中引入混沌机制,首先在混沌动态下搜索,然后利用HNN梯度优化搜索。对非线性函数的优化问题仿真表明算法具有很强的克服陷入局部极小能力。 相似文献
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一种混沌Hopfiele网络及其在优化计算中的应用 总被引:2,自引:1,他引:2
文章讨论了神经网络算法在约束优化问题中的应用,提出了一种混沌神经网络模型。在Hopfield网络中引入混沌机制,首先在混沌动态下搜索,然后利用HNN梯度优化搜索。对非线性函数的优化问题仿真表明算法具有很强的克服陷入局部极小能力。 相似文献
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非标定图像的最优匹配方法 总被引:2,自引:0,他引:2
该文将特征匹配和极线几何(epipolargeometry)估计有机地结合起来,给出了一种基于组合优化的非标定图像鲁棒匹配方法。通过灰度互相关计算得到初始候选匹配,然后使用该文提出的全局极线约束和局部视差约束代价函数,利用确定性退火方法同时估计匹配关系和基础矩阵。实验结果表明,此算法具有良好的鲁棒性,能够得到接近全局最优的匹配结果。 相似文献
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Kwanghoon Sohn Jung H. Kim Alexander W.E. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1998,28(1):82-90
This paper is an extension of our previous paper to improve the capability of detecting corners. We proposed a method of boundary smoothing for curvature estimation using a constrained regularization technique in the previous paper. We propose another approach to boundary smoothing for curvature estimation in this paper to improve the capability of detecting corners. The method is based on a minimization strategy known as mean field annealing which is a deterministic approximation to simulated annealing. It removes the noise while preserving corners very well. Thus, we can detect corners easier and better in this approach than in the constrained regularization approach. Finally, some matching results based on the corners detected by corner sharpness in the mean field annealing approach are presented as a demonstration of the power of the proposed algorithm. 相似文献
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提出了一种基于遗传模拟退火算法的启发式排样算法,并将这种算法应用于服装排样领域以减少原料的浪费。该算法通过基于遗传模拟退火算法的全局优化概率搜索,寻找排样件在排样时的最优次序及各自的旋转角度,然后采用基于左下角(BL)策略的启发式排样算法实现自动排样。 相似文献