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

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.