A machine vision system for seeds germination quality evaluation using fuzzy logic

This paper presents an automatic system for monitoring seed germination by means of a software tool incorporating an artificial vision system and a fu zzy logic-based classifier. The system employs a colour CCD camera to image trays in which seeds have been planted in cells and an image processing sy stem to identify the seedlings and their leaf area. This information enters a fuzzy logic-based classifier that simulates the quality grading of seedl ings undertaken by experienced technicians, based on their growth pattern. In some tests performed with three horticultural crops (lettuce, cauliflowe r and tomatoes), the fuzzy logic closely matched the evaluations made by te chnicians, thereby showing its potential to relieve them of a time-consumin g task. The system's associated database provides many possibilities for de cision support to the seed production industry. (C) 2001 Elsevier Science B .V. All rights reserved.