Roots image edge detection based on adaptive thresholds and wavelet transforms
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摘要: 植物根系的生長狀況可以反映該地區的氣候及土壤特性,現有的根系研究方法如挖掘法、整段標本法和剖面法,都有破壞樣本和工作量大等缺點.為了實時跟蹤植物根系生長狀況,介紹了一種基于多尺度小波變換和自適應閥值的圖像處理方法,對采用內窺方法獲得的根系圖像進行邊緣檢測,并將邊緣提取后的圖像進行融合.此方法可以在不損傷植物根系的前提下自動對根系的生長情況進行提取分析,實現實時采集及精確測量根系的物理參數.Abstract: The root's growing condition can reflect the climatic characteristics and soil status. Existing methods such as excavation, monolith and bisection will destroy the sample and have too much work to do. To track the root's growing addition in real time, this paper introduced a method based on adaptive thresholds and multiscale wavelet transforms, by which we can detect the edge of a root's image that obtained by endoscopy and then mosaic the images extracted from the edge. The method analyses the growing condition of the root automatically without any destroying. Through this system, we can acquire real-time collection and accurately measure the root's physical parameters.
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Key words:
- plant roots /
- image processing /
- edge detection /
- wavelet transforms /
- adaptive thresholds /
- endoscopy
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