Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

Article, Other literature type English OPEN
Thuy Tuong Nguyen ; David C. Slaughter ; Bradley D. Hanson ; Andrew Barber ; Amy Freitas ; Daniel Robles ; Erin Whelan (2015)
  • Publisher: MDPI AG
  • Journal: Sensors, volume 15, issue 8, pages 18,427-18,442 (issn: 1424-8220, eissn: 1424-8220)
  • Related identifiers: pmc: PMC4570329, doi: 10.3390/s150818427
  • Subject: perspective transform | plant counting | TP1-1185 | projection histogram | homography transform | tree crop enumeration | uncalibrated camera | Chemical technology | Article
    acm: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.
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