Automated vision recognition for classifying nutrient deficiencies based of elaeis guineensis leaf / Muhammad Asraf Hairuddin

Hairuddin, Muhammad Asraf (2014) Automated vision recognition for classifying nutrient deficiencies based of elaeis guineensis leaf / Muhammad Asraf Hairuddin. In: The Doctoral Research Abstracts. IPSis Biannual Publication, 6 (6). Institute of Graduate Studies, UiTM, Shah Alam.

[img]
Preview
Text
ABS_MUHAMMAD ASRAF HAIRUDDIN TDRA VOL 6 IGS_14.pdf

Download (395kB) | Preview

Abstract

Automated vision recognition has been widely implemented for various fields such as automobiles, manufacturing, medical, agricultural sector, etc. However, automation recognition specifically in oil palm or scientifically known as Elaeis Guineensis industry is still lacking. To the best of our knowledge, automatic detection device for nutrition-lacking disease based on appearance of symptoms on leaf surfaces is unavailable since at present, the disease is inspected by human experts depending on the knowledge and experience possessed. Hence, this thesis proposed to automate the nutritional disease detection due to nutritional deficiencies namely nitrogen, potassium and magnesium instead of manual visual recognition. This is because automation process is necessary to lessen error and reduce cost due to human experts as well as to increase speed of disease detection.

Item Type: Book Section
Creators:
CreatorsEmail
Hairuddin, Muhammad AsrafUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia
Divisions: Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: IPSis Biannual Publication
Volume: 6
Number: 6
Item ID: 19449
Uncontrolled Keywords: Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; Automated vision recognition
Last Modified: 11 Jun 2018 07:51
Depositing User: Staf Pendigitalan 2
URI: http://ir.uitm.edu.my/id/eprint/19449

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year