Classification of RFID-enabled Trajectory using Pattern Recognition Approach
Ying Shen, Weihua Zhu · International Journal of Signal Processing Image Processing and Pattern Recognition · 2014
RFID technology has been widely used in many fields. Lots of information could be obtained from the enormous RFID devices. Therefore, classification of the trajectory of these moving objects is significant to predict the trends of the moving objects. This paper introduces an innovative algorithm, using pattern recognition approach. This algorithm could be divided into several steps. First of all, the coarse-fine layer classification approach is used for clustering the trajectories. That aims to cut down the trajectories according to the difference phases. Secondly, in the sub-set of the trajectory, searching set is established through detecting the neighbor domains which have been classified at different phases. Finally, the hierarchical classification approach is used for classifying the sub-trajectory. By using the approach, the experimental results imply the feasibility and practicality of the proposed approach on figuring out the familiar trajectory of the RFID-enabled moving objects. It is observed that With the increasing of neighbor value, the linear trends is obvious from the figure, thus, the neighbor query decreases and the magnification ratio outperforms to TRACLUS method. Additionally, the proposed algorithm uses coarse-fine strategy at phases-to-phases, saving the time spend on large number of distance calculation at various phase.