Automating the plants growth monitoring By digital image processing

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Banna, Zein
Younis, Dana
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Monitoring plants growth is a real challenge in the field of agriculture .The complexity, effort, time and accuracy are critical factors for the tracking efficiency. In traditional context, discovering potential problems are likely to be late, as well for knowing the reasons behind, as a subsequent consequences, a latency in remedy actions. Automatic plants growth monitoring is an efficient method to lower the total effort of tracking and decision making. However, in practice, most plants monitoring methods focus on controlling the environment based on information from sensor devices regardless plants condition. This paper suggests using image processing techniques in extracting plants features i.e. (health, growth rate, condition...etc.) to help tracking plant's progress, care and access important gardening knowledge. The proposed techniques introduce image extraction using color spaces, color intensity, structural difference measure and k-means clustering for accurate plants conditions tracking. The test results from 60 sample of plants tracking show that the proposed methods manifest good level of accuracy and performance. Index Terms-Features extraction, Image processing, Plants monitoring.