We collect a multi-modality plant imagery database named “MSU-PID” including two types of plants: Arabidopsis and bean. It is captured using four types of imaging sensors:fluorescence, infrared(IR), RGB color, and depth. The imaging setup and the variety of manual labels allow MSU-PID to be used for a diverse set of plant image analysis applications, such as leaf segmentation, leaf counting, leaf alignment, and leaf tracking.

The database can be downloaded from here. It includes three parts:

  1. all images and their labels
  2. the leaf labeling tool
  3. the Matlab implementations for performance evaluation

Please cite the following paper if you use this database:

Publications

  • Multi-modality Imagery Database for Plant Phenotyping
    Jeffrey A. Cruz, Xi Yin, Xiaoming Liu, Saif M. Imran, Daniel D. Morris, David M. Kramer, Jin Chen
    Machine Vision and Applications, Vol. 7, pp.1-15, , Jul. 2016 (equal contribution by first two authors)
    Bibtex | PDF | Project Webpage
  • @article{ multi-modality-imagery-database-for-plant-phenotyping,
      author = { Jeffrey A. Cruz and Xi Yin and Xiaoming Liu and Saif M. Imran and Daniel D. Morris and David M. Kramer and Jin Chen },
      title = { Multi-modality Imagery Database for Plant Phenotyping },
      booktitle = { Machine Vision and Applications },
      volume = { 7 },
      month = { July },
      year = { 2016 },
      pages = { 1--15 },
    }