A new affine invariant descriptor for shape recognition

Shape is considered to be one of the most promising tools to represent and recognize an object. In this paper, an effective and rigorous shape descriptor is developed for shape recognition under affine transformations. To reflect the gray information of the shape, two extended centroids with different orders are adopted to form the vector which is treated as the x-axis to establish a new positively oriented orthonormal frame. Then, the descriptor representing the distribution of all points within the shape region along the y-axis is captured to achieve shape recognition. In addition to its stable affine invariance and robustness to noise, the descriptor has low computational complexity. The proposed descriptor has been implemented on a famous database and gives encouraging results while it is compared to other two state-of-the-art algorithms including GC and EC-ARC.