Liquid-level Estimation Using Region-based Segmentation for Automatic Beverage Refilling Service

Abstract

This paper presents an automatic liquid level detection algorithm for a beverage refilling service in a restaurant. The automatic detection of liquid level provides the amount of residual of customer's beverage using a general-purpose surveillance camera deployed in a restaurant. The proposed system consists of three modules i) extraction of a cup and beverage region using color-based region segmentation by K-means clustering, ii) edge detection of the cup and beverage region, and iii) liquid level estimation based on edge detection. Using a general-purpose CCTV camera and a set of relevant image processing algorithms, the proposed system can be one of important applications of internet of things (IoT) service.