A noncontact pH level sensing indicator using computer vision and knowledge-based systems

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management

Volume

2018-January

First Page

1

Last Page

5

Publication Date

7-2-2017

Abstract

A computer vision-based approach in identifying the pH level of a substance requires the use of multiple computer or machine vision techniques which include image processing, and object/contour detection, counting, or tracking. This paper proposes a pH level indicator system with knowledge-based systems (KBS) which has the capability of detecting, tracking, and identifying the level of a pH level indicator image. Moreover, the data that the system utilizes derives from KBS instead of being explicitly programmed. Furthermore, the study has a graphical user interface which allows the operator to easily use the system. The user may also add data to the knowledge-base, which means that the system improves over time. Compared with the traditional pH monitoring setup, the results in this study show that a computer vision-based approach is viable in determining the pH level of a substance. © 2017 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2017.8269474

Disciplines

Manufacturing | Mechanical Engineering

Keywords

Computer vision; Expert systems (Computer science); Hydrogen-ion concentration—Measurement--Automation

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