Estimation of Water Hyacinth Using Computer Vision

The different controls of water hyacinth, an invasive species tropical and subtropical environ-ments, have demonstrated some limitations requiring additional monitoring tasks to maintain the ecological balance. Therefore, quantifying valuing this aquatic biomass becomes a sustainable management alternative. However, hyacinth estimation remains challenging task in developing countries with regard used methods: empirical relationships between yield production indices calculated experimentally, structural parameters measured or through specific experiments (not dynamic), etc. These methods lose precision depending on type plant, cultural practices seasons. Then, it urgent develop dynamic method proven track record reliability despite inconsistency factors mentioned above. This article contributes improvement by proposing Computer Vision based solution for estimating fresh mass hyacinth. To achieve goal, morphology is assessed XML classifier developed. model then implemented mobile app facilitating its end use. proposed algorithm mean average 96.89%. Considering recorded level accurateness, developed can be estimate types biomass.