基于自适应阈值的k均值聚类手部图像分割

2017 7th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2017-11-01 DOI:10.1109/CSNT.2017.8418534

Sheifalee Trivedi, B. Nandwana, D. Khunteta, S. Narayan

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引用次数: 1

摘要

我们都知道，图像是一种描绘视觉感知的人工制品。为了提取信息或修改这些图像，我们必须对其进行一些操作。本文提出了一种基于阈值和直方图分析的改进k均值聚类方法对手图像进行分割。实验结果表明，该方法的准确率为97%，优于以往的方法。

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K-means clustering with adaptive threshold for segmentation of hand images

As we all know an image is an artifact that depicts visual perception. In order to extract information or modify those images we have to perform some operation on it. In this paper we present a methodology to segment hand images using modified k-means clustering with value of threshold and analysis of histogram. Experimental results show 97% accurate results so we can say proposed methodology is better then previous.

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2017 7th International Conference on Communication Systems and Network Technologies (CSNT)

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