Circle Detection System Using Image Moments

Rifqi Fachruddin, J. L. Buliali
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引用次数: 1

Abstract

The growth of system detection has significant development. The circle detection system is widely used to help people based on their needs, and it also could be used as learning media in educational fields. Especially for students with special needs, applying a circle detection system in Augmented Reality (AR) media would help them a lot. In order to make the study activity more effective and suit the learning material purpose, a circle detection system that only detects perfect full circles is needed to minimalize misconceptions in circle learning material. From the previous method such as Circle Hough Transform (CHT), circle detection faces the complex transition from cartesian coordinate into Hough coordinate. The use of image moments would give a coordinate of centroid that could use to find the radius by using the circle equation. Two groups of datasets would test the newly proposed method of detecting circles. Based on the experiment, the accuracy of the new method was 96.7%. The average time consumption is 0. 405 s which is faster than the CHT method with 1.024 s. Circle detection using image moments is also more robust towards noise than the previous CHT method.
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基于图像矩的圆检测系统
系统检测的增长有了显著的发展。圆检测系统广泛用于根据人们的需求提供帮助,也可以作为教育领域的学习媒介。特别是对于有特殊需求的学生,在增强现实(AR)媒体中应用圆圈检测系统将会对他们有很大的帮助。为了使学习活动更有效,更符合学习材料的目的,需要一个只检测完整圆的圆检测系统,以最大限度地减少对圆学习材料的误解。与以往的圆霍夫变换(CHT)等方法相比,圆检测面临着从直角坐标系到霍夫坐标系的复杂转换。利用像矩可以得到一个质心坐标,用这个质心坐标可以用圆方程求出半径。两组数据集将测试新提出的检测圆的方法。实验结果表明,新方法的准确率为96.7%。平均耗时为0。405 s,比CHT法的1.024 s快。使用图像矩的圆检测对噪声的鲁棒性也比以前的CHT方法强。
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