基于表面法线和元胞自动机的自由曲面重构

Reconstruction of freeform surface using needle map and cellular automata

通过2个阶段实现了从单目灰度图像重构自由曲面的过程:a.对表面法线通过3个约束条件进行逐步调整,光滑约束保证表面法线的光滑过度和可积性,灰度梯度约束确保重构所得的灰度梯度和原始图像的灰度梯度一致,灰度约束保证每点的法线满足光照模型;b.利用一个二维元胞自动机系统,从表面法线重构自由曲面,每个元胞具有自我决策能力,以表面法线为模板,根据自动机系统的自组织行为,实现自由曲面的重构.实验验证了本算法的可行性和准确性,与传统算法相比,重构精度至少提高30%.

A method for computing the depth of freeform surface from a single grayscale image in two steps is presented.The surface normals were parallelly and gradually adjusted by a procedure,which includes three constraints： smooth constraint ensures the recovered normals are smooth and integrable,intensity gradient constraint ensures the recovered normals are consistent with the image gradient field and intensity constraint guarantees the recovered intensity is equal to the input image.The surface was recovered from needle map using a two-dimensional cellular automata system.An experimental assessment is provided for our methods on both real world image and synthetic image with known ground truth.The experiment results demonstrate this approach is practicable and can improve reconstruction precision at least 30 % compared with traditional methods.