Title :
Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique
Author :
Ghazali, Kamarul Hawari ; Razali, Saifudin ; Mustafa, Mohd Marzuki ; Hussain, Aini
Author_Institution :
Fac. of Electr. & Electron. Eng., Univ. Malaysia Pahang, Kuantan
Abstract :
Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.
Keywords :
agriculture; computer vision; filtering theory; production engineering computing; agriculture industry; automatic weeding strategy; computer vision; image filtering technique; machine vision system; oil palm plantation; Application software; Computer industry; Computer vision; Filtering; Image processing; Lubricating oils; Machine vision; Manufacturing industries; Petroleum; Spraying; Automatic Weeding Strategy; Machinve vision; component; feature extraction; filter;
Conference_Titel :
Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on
Conference_Location :
Damascus
Print_ISBN :
978-1-4244-1751-3
Electronic_ISBN :
978-1-4244-1752-0
DOI :
10.1109/ICTTA.2008.4530075