Advanced Media Lab, Samsung Advanced Institute of Technology (SAIT), San14, Nongseo-dong, Giheung-gu, Yongin-si, Gyeonggi-do 446-712, South Korea.
IEEE Trans Pattern Anal Mach Intell. 2012 Feb;34(2):266-78. doi: 10.1109/TPAMI.2011.118.
We generalize the concept of bilateral reflection symmetry to curved glide-reflection symmetry in 2D euclidean space, such that classic reflection symmetry becomes one of its six special cases. We propose a local feature-based approach for curved glidereflection symmetry detection from real, unsegmented 2D images. Furthermore, we apply curved glide-reflection axis detection for curved reflection surface detection in 3D images. Our method discovers, groups, and connects statistically dominant local glidereflection axes in an Axis-Parameter-Space (APS) without preassumptions on the types of reflection symmetries. Quantitative evaluations and comparisons against state-of-the-art algorithms on a diverse 64-test-image set and 1,125 Swedish leaf-data images show a promising average detection rate of the proposed algorithm at 80 and 40 percent, respectively, and superior performance over existing reflection symmetry detection algorithms. Potential applications in computer vision, particularly biomedical imaging, include saliency detection from unsegmented images and quantification of deviations from normality. We make our 64-test-image set publicly available.
我们将双边反射对称的概念推广到二维欧几里得空间中的弯曲滑移反射对称，使得经典反射对称成为其六个特殊情况之一。我们提出了一种基于局部特征的方法，用于从真实的、未分割的二维图像中检测弯曲滑移反射对称。此外，我们还将弯曲滑移反射轴检测应用于三维图像中的弯曲反射面检测。我们的方法在没有对反射对称类型进行先验假设的情况下，在轴参数空间（APS）中发现、分组和连接统计上占主导地位的局部滑移反射轴。在一个包含 64 张测试图像和 1125 张瑞典叶片数据图像的多样化数据集上，与最先进的算法进行的定量评估和比较表明，该算法的平均检测率分别为 80%和 40%，性能优于现有的反射对称检测算法。在计算机视觉，特别是生物医学成像领域的潜在应用包括从未分割的图像中检测显著性和量化偏离正常情况。我们公开了我们的 64 张测试图像集。
