Legume Identification by Leaf Vein Images Classification

  • Mónica G. Larese
  • Roque M. Craviotto
  • Miriam R. Arango
  • Carina Gallo
  • Pablo M. Granitto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)


In this paper we propose an automatic algorithm able to classify legume leaf images considering only the leaf venation patterns (leaf shape, color and texture are excluded). This method processes leaf images captured with a standard scanner and segments the veins using the Unconstrained Hit-or-Miss Transform (UHMT) and adaptive thresholding. We measure several morphological features on the veins and classify them using Random forests. We applied the process to recognize several legumes (soybean, white bean and red bean). We analyze the importance of the features and select a small set which is relevant for the recognition task. Our automatic procedure outperforms the expert manual classification.


Leaf images automatic classification Legume automatic recognition Image analysis Random forests Unconstrained Hit-or-Miss Transform 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mónica G. Larese
    • 1
    • 2
    • 3
  • Roque M. Craviotto
    • 3
  • Miriam R. Arango
    • 3
  • Carina Gallo
    • 3
  • Pablo M. Granitto
    • 1
    • 2
  1. 1.CIFASIS, French Argentine International Center for Information and Systems SciencesUAMFrance
  2. 2.UNR-CONICETRosarioArgentina
  3. 3.Estación Experimental Oliveros, Instituto Nacional de Tecnología AgropecuariaOliverosArgentina

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