An Algorithm for Inspecting the Number of Self Check-In Airline Luggage Based on Hierarchical Clustering

Airport passengers are required to put only one baggage each time in the check-in self-service so that the baggage can be detected and identified successfully. In order to automatically get the number of baggage that had been put on the conveyor belt, dual laser rangefinders are used to scan the outer contour of luggage in this paper. The algorithm based on hierarchical clustering is proposed to inspect the number of airline luggage. Firstly, the laser point cloud data of the luggage surface is preprocessed to filter the background and noise. Secondly, the point cloud is projected to vertical direction. By the analysis of one-dimensional clustering, the number of luggage will be quickly computed. If it cannot be distinguished in this dimension, the method of nearest hierarchical clustering is applied to divide the point cloud. It can preferably solve the difficult issue like crossing or overlapping pieces of baggage. Finally, many experiments in different cases have been done to verify the effectiveness of the algorithm.