Liquid-level estimation using region-based segmentation for automatic beverage refilling service

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 s...

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Bibliographic Details
Published in2015 International Symposium on Consumer Electronics (ISCE) pp. 1 - 2
Main Authors Mikang Kim, Jinbeum Jang, Kyungwon Jeong, Daehee Kim, Joonki Paik
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2015
Subjects
Cameras
Clustering algorithms
Estimation
Image color analysis
Image edge detection
image processing
IoT
Liquids
service industry
Surveillance
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Summary: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.
ISSN:0747-668X
2159-1423
DOI:10.1109/ISCE.2015.7177811