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Leaf Segmentation, Its 3D Position Estimation and Leaf Classification from a Few Images with Very Close Viewpoints

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Image Analysis and Recognition (ICIAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

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Abstract

In this paper, we present a complete system to extract leaves, recover their 3D positions and finally classify them based on leaf shape. We use only a few images with slightly different viewpoints to achieve the task. The images are captured by a general hand-held digital camera and no camera pre-calibration is required. Because only a few images with close viewpoints are sufficient to segment the leaves and recover their 3D positions, our system is flexible and easy to use in image acquisition. For leaf classification, we use the normalized centroid-contour distance as our classification feature and employ a circular-shift comparing scheme to measure the similarity, thus our system has the advantages of being invariant to leaf translation, rotation and scaling. We have conducted several experiments and the results are encouraging. The leaves are nearly perfectly extracted and the classification results are also acceptable.

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Author information

Authors and Affiliations

  1. Department of Information Communication, Yuan Ze University, Taiwan

    Chin-Hung Teng

  2. Department of Electrical Engineering, Yuan Ze University, Taiwan

    Yi-Ting Kuo & Yung-Sheng Chen

Authors
  1. Chin-Hung Teng
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  2. Yi-Ting Kuo
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  3. Yung-Sheng Chen
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2009 Springer-Verlag Berlin Heidelberg

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Teng, CH., Kuo, YT., Chen, YS. (2009). Leaf Segmentation, Its 3D Position Estimation and Leaf Classification from a Few Images with Very Close Viewpoints. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_92

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  • DOI: https://doi.org/10.1007/978-3-642-02611-9_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02610-2

  • Online ISBN: 978-3-642-02611-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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