基于图像滤波技术的油棕种植园自动除草机器视觉系统

K. Ghazali, S. Razali, M. Mustafa, A. Hussain
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引用次数: 28

摘要

机器视觉是计算机视觉在工业、制造业或任何其他领域实现传统工作自动化的一种应用。目前,农业界已经开始着手研究工程技术在农业生产中的应用。自动除草是涉及机器视觉系统的精准农业活动之一。油棕种植园的自动除草策略可以最大限度地减少喷洒到田地的除草剂量。本文讨论了一种利用机器视觉系统对油棕种植园的杂草进行检测和鉴别喷洒的自动除草策略。视觉系统的实现涉及到利用图像处理技术对杂草图像进行分析,以识别和区分杂草的类型。采用图像滤波技术对图像进行处理,并采用特征提取方法对杂草图像进行分类。因此,图像处理技术为实现自动除草策略的机器视觉系统分类提供了良好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique
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.
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