关键词: 支持向量机, 选择分块, 电容层析成像, 数据预处理, 图像重建

Abstract: According to Support Vector Machine（SVM） has low training speed and low accuracy to deal with large scale data in Electrical Capacitance Tomography（ECT） system, a new algorithm that combined SVM with the Choice and Segmentation（CS） is presented and it comes into being a new classifier. Data in ECT system composes a data matrix which is fixed matrix column componented of sixty-six capacitance values and sixty-six sensitivity, the samples as its rows.It divides block selectively from large scale samples for one imaging unit. The numerical experiments show that the mixed algorithm can not only improve the accuracy compared to sole SVM, but also shorten time in imaging.

Key words: Support Vector Machine（SVM）, Choice and Segmentation（CS）, Electrical Capacitance Tomography（ECT）, data preprocessing, image reconstruction