Electrical Capacitance Tomography Sensor With House Structure for Assisting Recognition of Objects

Abstract

As a fast and non-invasive visualization technology, electrical capacitance tomography(ECT) avoids the problem that camera imaging technology is interfered by light and can’t identify material properties. However, the traditional ECT sensor research mainly focused on the image reconstruction of multiphase flow between electrodes, without considering the object recognition performance through the dielectric distribution of the objects. Therefore, we propose a new ECT sensor (called House Sensor) with house-like structure, which is suitable for multi features detection of household objects. We analyze the sensitivity distribution of House Sensor, and use linear back projection (LBP) and Tikhonov regularization for high-speed image reconstruction. 20 objects with different sizes and dielectric constants are visually clustered by t-distributed stochastic neighbor embedding (t-SNE) to verify the feasibility of classification, and the accuracy of Random Forest (RF) is up to 95.3% within 3.5ms. This implies that House Sensor provide a new feasible scheme to assist object recognition under non-vision conditions.