Automated brand inspection of plastic IC packages through computer vision using neural network

Date of Publication

1995

Document Type

Master's Thesis

Degree Name

Master of Science in Manufacturing Engineering

Subject Categories

Engineering

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Thesis Adviser

Kenneth Pinpin

Defense Panel Chair

Homer Co

Defense Panel Member

Nilo Bugtai
Tommy Lim

Abstract/Summary

The study is made to investigate the industrial applicability and performance of neural network-based computer vision system designed for inspection of actual brand images marked on top of IC packages. There were three devices considered in this thesis based on the limited and controlled number of these units provided by the company. Using the available limited samples of devises, brand names were captured using a camera and processed in the neural network using various representations to investigate thoroughly the effect of neural network parameters to network performance. As a result, using the neural network technique trained by backpropagation in brand defect recognition proved to be very effective within the scope and limitations of the concluded study.

Abstract Format

html

Language

English

Format

Print

Accession Number

TG02407

Shelf Location

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

Physical Description

77 numb. leaves

Keywords

Neural network; Computer vision; Brand name products; Plastics in packaging; Image processing; Quality control; Network analysis (Planning); Defect correction methods (Numerical analysis); xx6 Quality assurance

This document is currently not available here.

Share

COinS