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首页> 外文期刊>American Journal of Computational and Applied Mathematics >A Robust Method for Shape from Shading Using Genetic Algorithm Based on Matrix Code
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A Robust Method for Shape from Shading Using Genetic Algorithm Based on Matrix Code

机译:基于矩阵码的遗传算法稳健的阴影着色方法

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In this paper, a method for reconstructing a 3-D shape of an object from a 2-D shading image using a Genetic Algorithm (GA), which is an optimizing technique based on mechanisms of natural selection. The 3D-shape is recovered through the analysis of the gray levels in a single image of the scene. This problem is ill-posed except if some additional assumptions are made. In the proposed method, shape from shading is addressed as an energy minimization problem. The traditional deterministic approach provides efficient algorithms to solve this problem in terms of time but reaches its limits since the energy associated with shape from shading can contain multiple deep local minima. Genetic Algorithm is used as an alternative approach which is efficient at exploring the entire search space. The Algorithm is tested in both synthetic and real image and is found to perform accurate and efficient results.
机译:在本文中,一种使用遗传算法(GA)从2D阴影图像重建对象的3D形状的方法,这是一种基于自然选择机制的优化技术。通过分析场景的单个图像中的灰度来恢复3D形状。除非另作一些假设,否则这个问题是不适当的。在所提出的方法中,阴影引起的形状被解决为能量最小化问题。传统的确定性方法提供了有效的算法来解决该问题,但由于其与阴影产生的形状相关的能量可能包含多个深局部最小值,因此达到了极限。遗传算法用作替代方法,可以有效地探索整个搜索空间。该算法已在合成图像和真实图像中进行了测试,并且可以执行准确而有效的结果。

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