一种基于多维彩色向量空间的（火焰）图像模糊聚类分割算法

针对火灾探测过程中早期火焰的分割技术研究，文章提出了一种基于多维彩色向量空间的火焰图像模糊聚类分割算法，该算法以运动目标序列图像之间变化的区域作为聚类模板，提取该聚类模板的RGB多维彩色特征向量，然后将图像的像素与聚类模板通过模糊聚类的方式进行分割。这种分割算法计算简单，时间开销较小，可以较好的获取火焰图像的边缘形态特征，并且能够明显消除不同光线下分割误差，实现快速无监督自动分割。

A Fuzzy Clustering Segmentation Algorithm of Flame Image Based on Multi-Dimensional Color Vector Space Image Based on Multi-Dimensional Color Vector Space Based on Multi-Dimensional Color Vector Space

Process for the research of early fire segmentation technology, the article proposes a fuzzy clustering segmentation algorithm based on multi-dimensional color vector space. This algorithm uses the moving object image sequence variation region as a clustering template. When template is ready, its RGB eigenvectors are extracted and then the segmentation can be continued by using this clustering template. The arithmetic can be easily operated and time overhead. By this algorithm, a better picture of morphological characteristics of the flame edge can be obtained, the segmentation error under different light can significantly be eliminated, and fast unsupervised automatic segmentation can be completed.