A Modified Algorithm for a Density-based Clustering Method

Ze-Lu Deng, Jian-Bin Gao, Qi Xia

Abstract


We develop a fast algorithm for a density-based clustering method [1] when it is applied to gray image segmentation. To achieve this, we rely on the property that a gray image has no more than 256 gray levels. This will help us reduce the computing time by a factor of 300 while still keep the performance.

Keywords


Gray Image Segmentation, Clustering Method, Fast Algorithm


DOI
10.12783/dtcse/aice-ncs2016/5678

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