An automated self-adaptive paint mixing system using image processing

Date of Publication

1995

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Electronics and Communications Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Abstract/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.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU06845

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

115 leaves ; Computer print-out.

Keywords

Image processing; Electronic data processing--Distributed processing; Paint mixing; Digital electronics; Electronic digital computers; Automatic control

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