Date

4-2010

Degree

Bachelor of Science in Agricultural Engineering

Major Course

Major in Agricultural Power and Machinery Engineering

College

College of Engineering and Agro-Industrial Technology (CEAT)

Adviser/Committee Chair

Marvin C. Petingco

Committee Member

Rossana Marie C. Amongo, Pepito M. Bato

Abstract

A machine vision system,which consists of a Sony DCR-TRV 460 Digital Video Cam Recorder, an egg candling chamber, a TV capture card, a Pentium 4 personal computer at 2.66 Ghz speed, and software (EC 1.0) for determining duck egg fertility was developed and tested. Ten samples of 10-day old eggs were used to test the precision of the software in measuring the size of the egg at 24 orientation angles. On the other hand, 30, 20-day old egg samples (15 fertile and 15 infertile) and 30, 17-day old egg samples (15 fertile and 15 infertile) were used to test precision of the software in classifying the fertility of duck eggs. For the accuracy of the software in classifying the duck egg fertility, 30, 17-day old duck eggs were used. The results showed that the developed software has a 99.4 percent precision in measuring the size of the egg. The percent accuracies, using the expert's classification as standard, were 93.33% and 96.67% for the 10-day and 17-day old duck egg, respectively. The results showed a hundred percent accuracy in classifying the fertility of a 17-day old duck egg.

Language

English

LC Subject

Computer vision

Call Number

LG 993.5 2010 A2 J67

Document Type

Thesis

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