Area and volume measurements of objects with irregular shapes using multiple silhouettes

Abstract

Surface area and volume measurements provide important information for agriculture and food-processing applications. A machine vision system that uses a nondestructive method to measure volume and surface area of objects with irregular shapes is presented in this paper. The system first takes a series of silhouettes of the object from different directions by rotating the object at a fixed angular interval. The boundary points of each image are then extracted to construct a silhouette. A three-dimensional wire-frame model of the object can be reconstructed by integrating silhouettes obtained from different view angles. Surface area and volume can then be measured by means of surface fitting and approximation on the wire-frame model. System calibration and surface approximation were two major challenges for the design of this machine vision system. A unique centerline calibration method is introduced in this paper. Surface approximation and calculation are also discussed. Examples of applications in agriculture and food processing using this vision system for surface area measurement are included, and its accuracy is verified.