基于形状的不规则链码相似性医学图像检索方法

Byung K. Jung, Sung Y. Shin, Seong‐Ho Son, J. Pack
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引用次数: 1

摘要

本文提出了一种基于形状的图像检索方法,该方法基于表示物体不规则性的链码。引入独特的链码作为提取对象的主要特征。本文使用的所有目标都是由著名的分类算法支持向量机(SVM)提取的二值目标图像。从这些分类后的二值图像中,我们提出了一种改进的基于形状的图像检索方法,该方法使用唯一的链码来解释物体的不规则性。将该方法与已知的基于形状的图像检索方法结合特征点特征进行实验。实验结果表明,该方法的匹配率高于传统的等高线到质心三角剖分(CTCT)方法,具有较高的匹配率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shape based medical image retrieval method using irregularity chain code similarity
In this paper, we present a shape based image retrieval method based on chain code representing irregularity of an object. A distinctive chain code is introduced as a main extracted feature of the object. All objects used in this paper are binary object images extracted by well-known classification algorithm, Support Vector Machine (SVM). From these classified binary images, we propose a modified shape based image retrieval method with the unique chain code interpreting irregularity of object. Proposed method is experimented along with known shape based image retrieval method using characteristic point features. The experimental result shows that proposed method exceed matching rate that of conventional contour to centroid triangulation (CTCT) method showing proposed method has higher matching rate.
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