Water Reflection Detection Using a Flip Invariant Shape Detector
Hua Zhang, Xiaojie Guo, Xiaochun Cao · 2010
Water reflection detection is a tough task in computer vision, since the reflection is distorted by ripples irregularly. This paper proposes an effective method to detect water reflections. We introduce a descriptor that is not only invariant to scales, rotations and affine transformations, but also tolerant to the flip transformation and even non-rigid distortions, such as ripple effects. We analyze the structure of our descriptor and show how it outperforms the existing mirror feature descriptors in the context of water reflection. The experimental results demonstrate that our method is able to detect the water reflections.