ArcPSO: Ellipse detection method using particle swarm optimization and arc combination

Abstract

In this paper we present a technique for ellipse detection in digital images based on swarm intelligence algorithm and arc segment combination. The proposed method is then used as embryo quality scoring assessment during the first 24–48 hours since its morphological structure can be approximated by ellipse. The idea of the proposed algorithm are based on combining possible arcs for the ellipse shaped objects and try to find the best combinations using Particle Swarm Optimization technique to find the actual ellipse. The process involves detecting line segments in the image and then followed by arc segment extraction from lines to get potential elliptical arcs. The detection process is then guided by Particle Swarm Optimization (PSO) by utilizing the calculation of the fitness function from the arc segment that had been detected previously. The measurement results of proposed method are then compared with manual measurements. The experiment results were conducted on both synthetic data and real embryo images. Experiment results showed that the proposed method is better than several ellipse detection methods such as RHT, IRHT, and PSORHT to detect ellipses on the image. Another advantage of our proposed algorithm compared to the Hough Transform variants is that it can be used for multiple ellipse detection.