Analysis and performance evaluation of various image segmentation methods

S. U. Mageswari, C. Mala
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引用次数: 3

Abstract

Image segmentation is a primary stage in image processing for identifying objects of interest. Segmentation methods are classified into region based, transform based, edge based and clustering based segmentation. In this paper, segmentation methods including histogram, watershed, Canny edge detector and K-means clustering techniques are studied and analyzed. The experimental results obtained are compared with different evaluation measures including three standard image segmentation indices: rand index, globally consistency error and variation of information.
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各种图像分割方法的分析与性能评价
图像分割是图像处理中识别感兴趣对象的主要步骤。分割方法分为基于区域的、基于变换的、基于边缘的和基于聚类的。本文对直方图、分水岭、Canny边缘检测和k均值聚类等分割方法进行了研究和分析。采用兰德指数、全局一致性误差和信息变异三种标准图像分割指标对实验结果进行了比较。
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