Abstract
The problem we address in this paper is the segmentation and hierarchical grouping in digital images. In terms of image acquisition protocol, no constraints are posed to the user. At first, a histogram thresholding provides numerous segments where a homogeneity criterion is respected. Segments are merged together using similarity properties and aggregated in a hierarchy based on spatial inclusions. Shape and color features are extracted on the produced segments. Tests performed on Oxford Flower 17 [8] show that our method outperforms a similar one and allow the relevant object selection from the hierarchy. In our case, this approach represents the first stage towards flower variety identification.
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References
Rother, C., Kolmogorov, V., Blake, A.: GrabCut: Interactive Foreground Extraction using Iterated Graph Cuts. ACM Transactions on Graphics 23, 309–314 (2004)
Nilsback, M.-E., Zisserman, A.: Delving Deeper into the Whorl of Flower Segmentation. Image and Vision Computing 28(6), 1049–1062 (2010)
Chai, Y., Lempitsky, V., Zisserman, A.: BiCoS: A Bi-level Co-Segmentation Method for Image Classification. In: IEEE International Conference on Computer Vision, pp. 2579–2586 (2011)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient Graph-Based Image Segmentation. International Journal on Computer Vision 59(2), 167–181 (2004)
Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour Detection and Hierarchical Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(5), 898–916 (2011)
Akbas, E., Ahuja, N.: From Ramp Discontinuities to Segmentation Tree. In: Zha, H., Taniguchi, R.-i., Maybank, S. (eds.) ACCV 2009, Part I. LNCS, vol. 5994, pp. 123–134. Springer, Heidelberg (2010)
Todorovic, S., Ahuja, N.: Unsupervised Category Modeling, Recognition, and Segmentation in Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(12), 2158–2174 (2008)
Oxford Flowers 17 (2011), http://www.robots.ox.ac.uk/~vgg/data/bicos/
van de Sande, K., Uijlings, J., Gevers, T., Smeulders, A.: Segmentation as Selective Search for Object Recognition. In: IEEE International Conference on Computer Vision, pp. 1879–1886 (2011)
Cerutti, G., Tougne, L., Vacavant, A., Coquin, D.: A Parametric Active Polygon for Leaf Segmentation and Shape Estimation. In: International Symposium on Visual Computing, pp. 202–213 (2011)
Angelova, A., Zhu, S., Lin, Y.: Image segmentation for large-scale subcategory flower recognition. In: IEEE Workshop on the Applications of Computer Vision, pp. 39–45 (2013)
Kumar, N., Belhumeur, P.N., Biswas, A., Jacobs, D.W., John Kress, W., Lopez, I.C., Soares, J.V.B.: Leafsnap: A computer vision system for automatic plant species identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part II. LNCS, vol. 7573, pp. 502–516. Springer, Heidelberg (2012)
Chai, Y., Rahtu, E., Lempitsky, V., Van Gool, L., Zisserman, A.: TriCoS: A tri-level class-discriminative co-segmentation method for image classification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part I. LNCS, vol. 7572, pp. 794–807. Springer, Heidelberg (2012)
Singh, G.: Plants Systematics: An Integrated Approach. Science Publishers (2004)
Folia (2011), http://liris.cnrs.fr/reves/index.php
Leafsnap (2011), http://leafsnap.com/
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Suta, L., Scuturici, M., Scuturici, VM., Miguet, S. (2013). PaTHOS: Part-Based Tree Hierarchy for Object Segmentation. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_47
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DOI: https://doi.org/10.1007/978-3-642-40261-6_47
Publisher Name: Springer, Berlin, Heidelberg
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