AnImproved Edge Detector Based on Superpixel

摘要：

　　Edge is a significant feature for many computer vision applications.Existing edge detectors obtain a dense edge map depended on the contrast and gradient cues in an image.However, the dense edge map not only restricts the efficiency of subsequent vision tasks, but also may contain several edges located in background.In this paper, we propose a sparse edge detector by exploiting the boundary adherence of superpxiel.We first obtain original edge response and superpixel segmentation from Structured Edge Detector (SED) and Simple Linear Iterative Clustering (SLIC) separately.Then a simplifying operation is exerted on the original edge map according to the border guidance of superpixel.Extensive experiments on BSDS500 dataset demonstrate that the proposed method achieves a sparse and discriminative edge detector.

关键词： Edge Detector Boundary-preserving Superpixel Improvement

作者: Zhao Hao Wang Jikai Dai Deiyun Chen Zonghai

作者单位: Department of Automation, University of Science and Technology of China,Anhui, Hefei, 230026

会议类型: 国内会议

会议名称: 第20届中国系统仿真技术及其应用学术年会(20th CCSSTA 2019)

会议地点: 合肥

会议语种:英文

页码: 578-582

在线出版日期: 2019-08-01（万方平台首次上网日期，不代表论文的发表时间）