A new dominant point detection technique for polygonal approximation of digital planar closed curves. (22nd December 2020)

• Record Type: Journal Article
• Authors: Kalaivani, S.; Ray, Bimal Kumar
• Is Part Of: International journal of intelligent enterprise. Volume 8:Number 1(2021)
• Page Start: 44
• Page End: 61
• Publication Date: 2020-12-22
• Subjects: irregular polygon -- collinear points -- dominant point -- local deviation -- global deviation -- distortion error -- split -- merge -- polygonal approximation; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Business intelligence -- Periodicals; Business enterprises -- Design -- Periodicals; Organizational effectiveness -- Periodicals; 658.005
• Languages: English
• ISSNs: 1745-3232

Abstract

On the visual perception, the real-world objects are the collection of irregular polygons. Representation and understanding the irregular polygon is an interesting and major task in various research areas. However, an approximation of the polygon is quite complex and challenging in different views. In this paper, a new approximation algorithm is proposed to represent the irregular polygon. Using centroid most of the weak points are suppressed and elimination of noise is integrated to produce better results. Iterative insertion of the dominant point is followed with suppression until the required approximation. The proposed method detects the dominant points which have a high impact on the shape and suppress the weak points. The obtained approximated polygon is with fewer vertices/points and retain the original shape with less approximation error. The experiments of the proposed algorithm are conducted using MPEG shape datasets to show its performance both in quantitative and qualitative aspect.