Acceleration of CT reconstruction for wheat tiller inspection based on adaptive minimum enclosing rectangle

  • Authors:

  • Ni Jiang;Wanneng Yang;Lingfeng Duan;Xiaochun Xu;Chenglong Huang;Qian Liu

  • Affiliations:

  • Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...;Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...;Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...;Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...;Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...;Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, PR China and Key Laborato ...

  • Venue:
  • Computers and Electronics in Agriculture
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 11870ms to less than 200ms. In sum, the optimized method met the requirement of real-time imaging and expanded CT application in plant phenomics and agriculture photonics.