Evaluating a Machine Vision System by Measuring Some Physical Characteristics of Pistachio Nuts

Abstract:

In order to increase the role of machine vision in agricultural research in Iran, especially for measuring physical attributes of seeds, a machine vision system was developed using a computer, a capture card, a video camera and a light box. All equipment was purchased from domestic markets. Computer programs were developed for hardware setup and for image processing applications. The programs perfomed tasks such as image acquisition and display, color conversion, image segmentation, object counting, and measurement of some physical attributes of the objects by analysing their images. The system was used to measure some physical attributes of pistachio nuts. The machine vision measurements were statistically compared with the measurements obtained by the conventional manual methods. The results indicated that there was generally no significant difference between the two methods. However, the time consumed by the machine vision method was far less than the time taken by manual methods. The experimental results also showed that there were many sources of error and limiting factors in using machine vision for measuring physical attributes of seeds.

Language:
Persian
Published:
Journal of Hydrology and Soil Science, Volume:7 Issue: 3, 2003
Page:
245
magiran.com/p644160  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!