A novel approach for color image segmentation using iterative partitioning mean shift clustering algorithm

P Pedda Sadhu Naik, T. Gopal
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引用次数: 7

Abstract

Segmentation is a process of partitioning the image into several objects. It plays a vital role in many fields such as satellite, remote sensing, object identification, face tracking and most importantly medical applications. Here in this paper, we here supposed to propose a novel image segmentation using iterative partitioning mean shift clustering algorithm, which overcomes the drawbacks of conventional clustering algorithms and provides a good segmented images. Simulation performance shows that the proposed scheme has performed superior to the existing clustering methods.
一种基于迭代分割均值偏移聚类算法的彩色图像分割新方法
分割是将图像分割成若干个对象的过程。它在卫星、遥感、目标识别、人脸跟踪以及最重要的医疗应用等许多领域发挥着至关重要的作用。本文提出了一种新的基于迭代分割均值偏移聚类算法的图像分割方法,克服了传统聚类算法的不足,提供了良好的分割图像。仿真结果表明,该方法优于现有的聚类方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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