Huang Ronggang, Liu Yiguang, Zheng Yunan, Ye Mao
Opt Express. 2020 Jun 22;28(13):18577-18595. doi: 10.1364/OE.390224.
Detecting an object using rotation symmetry property is widely applicable as most artificial objects have this property. However, current known techniques often fail due to using single symmetry energy. To tackle this problem, this paper proposes a novel method which consists of two steps: 1) Based on an optical image, two independent symmetry energies are extracted from the optical frequency space (RSS - Rotation Symmetry Strength) and phase space (SSD - Symmetry Shape Density). And, an optimized symmetry-energy-based fusion algorithm is creatively applied to these two energies to achieve a more comprehensive reflection of symmetry information. 2) In the fused symmetry energy map, the local region detection algorithm is used to realize the detection of multi-scale symmetry targets. Compared with known methods, the proposed method can get more multiple-scale (skewed, small-scale, and regular) rotation symmetry centers, and can significantly boost the performance of detecting symmetry properties with better accuracy. Experimental results confirm the performance of the proposed method, which is superior to the state-of-the-art methods.
利用旋转对称特性检测物体具有广泛的适用性，因为大多数人造物体都具备这一特性。然而，目前已知的技术由于使用单一对称能量，常常失效。为解决这一问题，本文提出一种新颖的方法，该方法包括两个步骤：1）基于光学图像，从光学频率空间（RSS - 旋转对称强度）和相位空间（SSD - 对称形状密度）中提取两个独立的对称能量。并且，一种基于对称能量的优化融合算法被创造性地应用于这两种能量，以更全面地反映对称信息。2）在融合后的对称能量图中，使用局部区域检测算法来实现多尺度对称目标的检测。与已知方法相比，所提方法能够获得更多多尺度（倾斜、小尺度和规则）旋转对称中心，并且能够显著提高对称特性检测的性能，具有更高的准确性。实验结果证实了所提方法的性能，其优于现有最先进的方法。
