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.