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A novel approach for unsupervised image segmentation fusion of plant leaves based on G-mutual information

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Abstract

Plant leaf segmentation has a very important role in most plant identification methods. Tree leaves segmentation in images with complex background is very difficult when there is no prior information about the leaves and backgrounds. In practice, the parameters of unsupervised image segmentation algorithms must be set for each image to get the best results. In this paper, to overcome this problem, fusion of the results of five leaf segmentation algorithms (fuzzy c-means, SOM and k-means in various color spaces or different parameters) is applied. To fuse the results of these segmentations, new equations for mutual information (g-mutual information equations) based on the g-calculus are introduced to find the best consensus segmentation. The results of the mentioned primary clustering algorithms are considered as a new feature vector for each pixel. To reduce the time complexity, a fast method is employed using truth table containing different feature vectors. To evaluate this new approach, a leaf image database with natural scenes, taken from Pl@ntLeaves database, is generated to have different positions and orientations. In addition, a widely used database is used to compare the proposed method with other methods. The experimental results presented in this paper show that the use of g-calculus in fusion of image segmentations improves the evaluation parameters.

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Acknowledgement

The authors acknowledge the funding support of Babol Noshirvani University of Technology through Grant program Nos. BNUT/370123/99 and BNUT/392100/99.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Shariati Ave, Babol, 47148-1167, Iran

    Navid Nikbakhsh & Yasser Baleghi

  2. Department of Mathematics, Faculty of Basic Science, Babol Noshirvani University of Technology, Shariati Ave, Babol, 47148-71167, Iran

    Hamzeh Agahi

Authors
  1. Navid Nikbakhsh
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  2. Yasser Baleghi
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  3. Hamzeh Agahi
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Correspondence to Yasser Baleghi.

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Nikbakhsh, N., Baleghi, Y. & Agahi, H. A novel approach for unsupervised image segmentation fusion of plant leaves based on G-mutual information. Machine Vision and Applications 32, 5 (2021). https://doi.org/10.1007/s00138-020-01130-0

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