Journal of Food, Agriculture and Environment

Recognition of weed seed species by image processing

Author(s):

Arman Arefi ^1*, Asad Modarres Motlagh ¹, Alireza Khoshroo ²

Recieved Date: 2010-10-07, Accepted Date: 2011-01-19

Abstract:

Recently, in order to increase the speed detection of seeds, the methods based on computer vision is expanded. Since, some characteristics such as colour, morphology and texture show the difference of objects. Therefore, it is necessary that these parameters should be used by machine vision for reorganization of different objects from each other. In this study, identification of four major weed seeds (common vetch, cleavers, cornflower and great bur-parsley), that are widely found in farms of West and North West of Iran, was done by digital image analysis. Recognizing and removing the weed seeds from the main product is very important. By recognizing the weed seed species from each other, it is possible to determine the percentage of farm pollution to each of weed seeds, and then weed control operations will be applied. The value of products is determined through ratio of weed seeds weight to total weight. Therefore, recognition of weed seed species as the first step in determination of products value is very important. For this purpose, by using a chamber of imaging, some uniform images of samples were acquired. Then, a program was coded in Matlab software for segmentation of the samples. Recognition of weed seeds was based on morphology and colour. For recognizing common vetch, great bur-parsley and cornflower colour features defined in RGB and HSI colour models were used. These colour features were mean (red), mean and variance of saturation component. Recognition of cleavers was done by two morphology features, Shape factor 1 and Shape factor 2. According to the results, total classification accuracy was 98.40%. This shows that the system has great potential to serve as an intelligent recognition system in real applications.

Keywords:

Weed seed, image processing, machine vision, variety identification

---

Journal: Journal of Food, Agriculture and Environment
Year: 2011
Volume: 9
Issue: 1
Category: Agriculture
Pages: 379-383

---

Full text for Subscribers

---

Information:

Note to users

The requested document is freely available only to subscribers/registered users with an online subscription to the Journal of Food, Agriculture & Environment. If you have set up a personal subscription to this title please enter your user name and password. All abstracts are available for free.

Article purchasing

If you like to purchase this specific document such as article, review or this journal issue, contact us. Specify the title of the article or review, issue, number, volume and date of the publication. Software and compilation, Science & Technology, all rights reserved. Your use of this website details or service is governed by terms of use. Authors are invited to check from time to time news or information.

---

Purchase this Article:   20 Purchase PDF Order Reprints for 15

---

Share this article :