کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
85064 | 158921 | 2012 | 11 صفحه PDF | دانلود رایگان |

Tiller number is highly correlated with grain yield in wheat. Traditional observation of wheat tiller number is still manual. Previously, our group developed a high-throughput system for measuring automatically rice tillers (H-SMART) based on X-ray computed tomography (CT), providing high accuracy for measuring rice tillers. However, the time-consuming reconstruction, which is necessary to generate tomographic images, limits the throughput improvement of system as well as the CT potential for the real-time applications. In order to accelerate the reconstruction process, we present an adaptive minimum enclosing rectangle (AMER) method to reduce the number of reconstructed pixels from the full field of view (FOV) and apply parallel processing using Graphics Processing Unit (GPU). The reconstruction time and speedup with different methods were discussed. Compared to the AMER method, GPU technique improved reconstruction with a higher speedup of approximately 200 times. And the speedup with AMER method was determined by two factors: area ratio of AMER and FOV, and the longest distance between the vertices of the AMER and the rotation center. Besides reconstruction, tiller identification could also be accelerated by AMER. Moreover, the tiller measurement accuracy did not decrease. With the combination of AMER and GPU, the entire tiller inspection time for a pot-grown plant was reduced from about 11870 ms to less than 200 ms. In sum, the optimized method met the requirement of real-time imaging and expanded CT application in plant phenomics and agriculture photonics.
► The GPU-based CT reconstruction algorithm using AMER method can accelerate the CT reconstruction.
► GPU technique improved reconstruction with a speedup of approximately 200 times.
► The speedup with AMER method was mainly determined by the area ratio of AMER and FOV.
► The entire tiller inspection time for a pot-plant was reduced from about 11870 ms to less than 200 ms.
► The tiller measurement accuracy did not decrease after applying the method.
Journal: Computers and Electronics in Agriculture - Volume 85, July 2012, Pages 123–133