An efficient ellipse detector based on region detection and arc pruning
Tian Xie, Ruike Zhang, Jingchao Liang, Qi Jia, Xin Fan, Zhongxuan Luo
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Detecting ellipses accurately and efficiently for real-world images is crucial for various visual-based applications. Most existing methods employ detection strategies throughout images, while most time is spent on the non-ellipse region. Meanwhile, small ellipses are often miss-detected due to the low resolution and fixed parameters of detectors. In this paper, we proposed an effective ellipse detector benefiting from the region detection method, which provides a basic estimation on the region and size of ellipses. Then, a two-level arc pruning strategy is proposed to detect ellipses efficiently while limiting false-positive and false-negative results. Furthermore, for the pre-estimated region without detected ellipses, interpolation method is employed to enlarge the target region, which makes small and blur ellipses to be detected. Experimental results demonstrate that the proposed method achieves competitive accuracy compared with the state-of-the-art methods.