Evaluation and review of several color indices used for segmenting plant from non-plant regions in color images

The main part of a machine vision system is to distinguish the object of interest (in the case of this project, a plant) from non-important regions (we refer it as background). Distinguishing the objects of interest is simplified if the high contrast between the objects of interest and background is created. The objective of this study is to find the best color index by which the algorithm is able to create the highest contrast between plant and non-plant regions. For this study, images were taken of varying numbers of wheat plants under several growth stages in a loamy sand soil and in diffused light condition. Three regions were predefined on the images; plant, pebble, and soil regions. Regions for plants, soil and pebbles were separately cropped within each image, aiming to provide a pooled representation for each object in each image. For each image, 13 mean color index were computed for each the three regions of interest (plant, soil, and pebble). The results of applying Analysis of variance (ANOVA) and consequently t-tests indicated that modified Excessive Green Index (MEGI) can potentially make the highest contrast between plant and non-plant regions rather than other color indices.

کلیدواژه ها:

Computer vision system ، image analysis ، color plant segmentation ، color indices