Corner detection using the point‐to‐centroid distance technique. Issue 14 (13th October 2020)

• Record Type: Journal Article
• Authors: Zhang, Shizheng; Huangfu, Luwen; Zhang, Zhifeng; Huang, Sheng; Li, Pu; Wang, Heng
• Is Part Of: IET image processing. Volume 14:Issue 14(2020)
• Page Start: 3385
• Page End: 3392
• Publication Date: 2020-10-13
• Subjects: computer vision -- edge detection -- object tracking; corner detection -- corner sharpness -- corner detector -- contour‐based corner detectors -- point‐to‐centroid distance technique -- corner finding -- object tracking -- vehicle detection -- efficient corner detectors; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2020.0164
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Corners, highly important local features of images and corner finding, play a crucial role in computer vision and image processing, such as object tracking and vehicle detection. Proposing effective and efficient corner detectors is the aim of corner detection. In this study, the authors first present a new measure of corner sharpness termed as the point‐to‐centroid distance (PCD) and then examine its behaviours, which display beneficial characteristics that help distinguish corners from non‐corners. Based on PCD behaviours, the authors propose a novel corner detector. Extensive experimental results demonstrate that the PCD technique is effective and simultaneously efficient for corner detection compared with six other contour‐based corner detectors in terms of two commonly used evaluation metrics – average repeatability and localisation error.