改进基于图的图像分割方法

Ming Zhang, R. Alhajj
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引用次数: 23

摘要

传感器设备广泛用于监测目的。图像挖掘技术通常用于从传感器设备拍摄的图像序列中提取有用的知识。图像分割是图像挖掘的第一步。由于传感器设备的资源有限,我们需要时间和空间有效的图像分割方法。在本文中,我们对文献中描述的基于图的图像分割方法进行了改进,该方法被认为是最有效的方法,分割结果令人满意。这是我们的在线图像挖掘方法的预处理步骤。我们通过重新定义用于定义组件属性的内部差异和阈值函数来贡献该方法,阈值函数是确定组件大小的关键因素。实验证明了该方法的有效性和有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the Graph-Based Image Segmentation Method
Sensor devices are widely used for monitoring purposes. Image mining techniques are commonly employed to extract useful knowledge from the image sequences taken by sensor devices. Image segmentation is the first step of image mining. Due to the limited resources of the sensor devices, we need time and space efficient methods of image segmentation. In this paper, we propose an improvement to the graph-based image segmentation method already described in the literature and considered as the most effective method with satisfactory segmentation results. This is the preprocessing step of our online image mining approach. We contribute to the method by re-defining the internal difference used to define the property of the components and the threshold function, which is the key element to determine the size of the components. The conducted experiments demonstrate the efficiency and effectiveness of the adjusted method
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