Cultural Heritage (CH) artifacts generally possess symmetry of reflection, rotation, translation and glide reflection in their shape. Similarity measures are used to determine complex 3D models where symmetry is considered to be one of the similarity signatures. This work presents the methodology of detecting symmetry in 3D objects based on the three techniques: (1) Eigenvalues and Eigenvectors, (2) local surface discontinuity, and (3) pixel orientation. In this work, these methods have been modified suitably for the detection of symmetry in CH artifacts. Among these methods, it is found that the first two methods yield better performance on the symmetry signature estimation of 98 percent for complex models and up to 100% for primitive models. The execution time of the proposed methods is compared with the state-of-the-art approaches available in the literature. Three levels of random 3D models available in the internet repository are analyzed for efficiency, performance and robustness. At each level, the accuracy of the Eigenvalue method and the local discontinuity method is found to be better than the pixel orientation method. The modified algorithms have been tested for better performance with F-score, robustness, and execution time with 3D benchmark dataset and cultural heritage dataset available in the literature. Future work shall be extended by applying the symmetry features as constraints for the effective search of CH artifacts in digital repositories.

文化遗产（CH）工件通常在形状上具有反射，旋转，平移和滑行反射的对称性。相似性度量用于确定复杂的3D模型，其中对称性被视为相似性签名之一。这项工作提出了基于三种技术的3D对象对称性检测方法：（1）特征值和特征向量，（2）局部表面不连续性，以及（3）像素方向。在这项工作中，对这些方法进行了适当的修改，以检测CH伪像中的对称性。在这些方法中，发现前两种方法在对称模型的对称签名估计方面具有更好的性能，对于复杂模型而言为98％，对于原始模型则高达100％。将所提出的方法的执行时间与文献中提供的最新方法进行了比较。分析了Internet存储库中可用的三个级别的随机3D模型的效率，性能和鲁棒性。在每个级别上，特征值方法和局部不连续性方法的准确性都比像素定向方法要好。修改后的算法已经过测试，具有更好的性能使用文献中提供的3D基准数据集和文化遗产数据集获得F分数，鲁棒性和执行时间。通过使用对称性特征作为对数字存储库中的CH伪像的有效搜索的约束条件，可以扩展以后的工作。