An automated self-adaptive paint mixing system using image processing
With the recent technological advancements in the field of computers and electronics, almost all tasks done by humans are now being replaced by these machines which are capable of doing the job more efficiently. In almost any field, automation is taking a giant leap which could significantly increas...
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| Main Authors: | , , , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
1995
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/7454 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | With the recent technological advancements in the field of computers and electronics, almost all tasks done by humans are now being replaced by these machines which are capable of doing the job more efficiently. In almost any field, automation is taking a giant leap which could significantly increase job performance and production. The project study presented here is also geared towards the abovementioned trends in the industries. The Automated Self-Adaptive Paint Mixing System uses no human effort in mixing paints. With the use of a microcomputer which would control the whole system, the paint mixing system is capable of mixing the desired paint color samples. Digital Image Processing and Neural Networks are the main theme of the study. Through the use of a video camera, paint samples are seen by the system. The images stored are processed using digital image processing. These images are used as inputs for the neural network to determine the correct paint color combination. As such, the determination of the correct paint color sample as seen by the system is achieved with the use of Neural networks with BackPropagation (BPN) as the learning technique. The microcomputer is the one responsible for controlling the amounts of paint to be mixed. |
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