Title

Neural networks vision system for an automated tuna quality sorter

Date of Publication

2001

Document Type

Master's Thesis

Degree Name

Master of Science in Manufacturing Engineering

Subject Categories

Engineering Education

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Thesis Adviser

Elmer P. Dadios

Defense Panel Chair

Homer Co

Defense Panel Member

Alvin Chua
Edwin Sybingco

Abstract/Summary

This paper aims to develop the applicability of using Vision System and Neural Networks using a PC-based software to control an off-line multi-input, multi-input automated tuna quality sorting system. Initially, tuna is loaded on a belt conveyor running at a constant speed. Each time a tuna passes a first set of photo-sensors, a video camera installed overhead is triggered to capture its image. The captured image of the tuna is transformed into a data using image-processing algorithms, processed and analyzed by an IBM-PC that determines the quality of the tuna. As the belt conveyor continuously moves toward the end of the line, the tuna again passes another set of sensors that activate the flipper arm to move on the desired position and allow the tuna to slide to its corresponding bin.

Abstract Format

html

Language

English

Format

Print

Accession Number

TG03204

Shelf Location

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

Physical Description

89 numb. leaves ; 28 cm.

Keywords

Neural networks (Computer science); Automation; Image processing--Digital techniques; Sorting devices; Assembly-line methods; Manufacturing processes

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