Skip to main content
SpringerLink
Log in

Semantic-based automatic structuring of leaf images for advanced plant species identification

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Structuring the search space based on domain-specific vocabulary (or concepts) is capital for enhanced image retrieval. In this paper, we study the opportunities and the impact of exploiting such a strategy in a particular problem which is the leaf species identification. We believe that such a solution is promising to reduce the effect of the high variability across and within species and define more specific and relevant leaf image representations. Among botanical concepts that describe leaves (and particularly their architecture), we focus mainly on three of the most basic and commonly-used concepts: the leaf arrangement, lobation and partition. These concepts define two different structuring types: (1) One is a coarse categorisation of leaf datasets into three subsets, namely simple lobed, simple not lobed and compound (2) The other is a decomposition of the entire leaf images into semantic regions (or parts). We perform the whole structuring process automatically by defining simple geometric parameters (extracted from the leaf contour) based on the analysis of botanical definitions. A fine recognition process is then established in order to determine the species identity. It is defined, typically, using standard (texture or contour) descriptors followed by a KNN classifier. Enriched by the proposed structuring process, the search for species candidates will be restricted to the correspondent category of the query and based on a fusion of each part responses. Experiments carried out on the Scan Pictures of the ImageCLEF 2011 dataset (3070 images totalling 70 species) have shown an increase in performances for different descriptor configurations compared to global leaf representations as well as to some recent related studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26

Similar content being viewed by others

References

  1. Backes AR, Bruno OM (2010) Plant leaf identification using color and multi-scale fractal dimension. Comput Sci 6134:463–470

    Google Scholar 

  2. Backes AR, Casanova D, Bruno OM (2009) A complex network-based approach for boundary shape analysis. Pattern Recogn 42:54–67

    Article  Google Scholar 

  3. Bama B, Valli S, Raju S, Kumar V (2011) Content based leaf image retrieval (cblir) using shape, color and texture features. Indian J Comput Sci and Eng 202–211

  4. Beghin T, Cope JS, Remagnino P, Barman S (2010) Shape and texture based plant leaf classification, pp 345–353

    Chapter  Google Scholar 

  5. Casanova D, de Mesquita S, Junior JJ, Bruno OM (2009) Plant leaf identification using gabor wavelets. Int J Imaging Syst Technol

    Article  Google Scholar 

  6. Cerutti G, Tougne L, Mille J, Vacavant A, Coquin D (2013) A model-based approach for compound leaves understanding and identification. In: IEEE international conference on image processing

  7. Cerutti G, Tougne L, Vacavant A, Coquin D (2011) A parametric active polygon for leaf segmentation and shape estimation. In: Proceedings of the 7th international conference on Advances in visual computing - Volume Part I, pp 202–213

    Chapter  Google Scholar 

  8. Chi YT, Chien CF, Lin TT (2003) Leaf shape modeling and analysis using geometric descriptors derived from bezier curves. Trans ASAE 46:175–185

    Google Scholar 

  9. Cope JS, Corney D, Clark JY, Remagnino P, Wilkin P (2012) Review: Plant species identification using digital morphometrics: A review. Expert Syst Appl 7562–7573

    Article  Google Scholar 

  10. Cope JS, Remagnino P, Barman S, Wilkin P (2010) Plant texture classification using gabor co-occurrences. In: Proceedings of the 6th international conference on advances in visual computing - Volume Part II, pp 669–677

    Chapter  Google Scholar 

  11. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition, 2005. CVPR 2005

  12. Ferecatu M (2005) Image retrieval with active relevance feedback using both visual and keyword-based descriptors. Ph.D. thesis, Université de Versailles Saint-Quentin-en-Yvelines

  13. Florindo JB, Backes AR, Bruno OM (2010) Leaves shape classification using curvature and fractal dimension. Comput Sci 6134:456–462

    Google Scholar 

  14. Goëau H, Bonnet P, Joly A, Boujemaa N, Barthelemy D, Molino JF, Birnbaum P, Mouysset E, Picard M (2011) The clef 2011 plant images classification task. In: Working notes of CLEF 2011 conference (2011)

  15. Goëau H, Joly A, Selmi S, Bonnet P, Mouysset E, Joyeux L (2011) Visual-based plant species identification from crowdsourced data. In: ACM multimedia

  16. Group.65p LAW (Unknown Month 1999) Manual of Leaf Architecture. Department of Paleobiology Smithsonian Institution, Cornell University Press

  17. Gu X, Du JX, Wang X (2005) Leaf recognition based on the combination of wavelet transform and gaussian interpolation. In: ICIC (1)

    Google Scholar 

  18. Haibin GA, Agarwal G, Ling H, Jacobs D, Shirdhonkar S, Kress WJ, Russell R, Belhumeur P, Dixit A, Feiner S, Mahajan D, Sunkavalli K, Ramamoorthi R, White S (2006) First steps toward an electronic field guide for plants. Taxon 55:597–610

    Article  Google Scholar 

  19. Hearn DJ (2009) Shape analysis for the automated identification of plants from images of leaves. Taxon:934–954

  20. Hu RX, Jia W, Ling H, Huang D (2012) Multiscale distance matrix for fast plant leaf recognition. IEEE Trans Image Process

  21. JinKyu P, EenJun H, Yunyoung N (2008) Utilizing venation features for efficient leaf image retrieval. J Syst Softw 81:71–82

    Article  Google Scholar 

  22. Jovi M, Hatakeyama Y, Dong F, Hirota K (2006) Image retrieval based on similarity score fusion from feature similarity ranking lists. In: Fuzzy systems and knowledge discovery, lecture notes in computer science, vol 4223. Springer Berlin Heidelberg, pp 461–470

  23. Kumar N, Belhumeur P, Biswas A, Jacobs D, Kress W, Lopez I, Soares J (2012) Leafsnap: a computer vision system for automatic plant species identification. In: Computer Vision ECCV 2012, Lecture Notes in Computer Science, pp 502–516

    Chapter  Google Scholar 

  24. Mokhtarian F, Abbasi S (2004) Matching shapes with self-intersections:application to leaf classification. IEEE Trans Image Process 13:653–661

    Article  Google Scholar 

  25. Mokhtarian F, Mackworth A (1986) Scale-based description and recognition of planar curves and two-dimensional shapes. IEEE Trans Pattern Anal Mach Intell PAMI-8:34–43

    Article  Google Scholar 

  26. Mokhtarian F, Mackworth AK (1992) A theory of multiscale, curvature-based shape representation for planar curves. IEEE Trans Pattern Anal Mach Intell 14:789–805

    Article  Google Scholar 

  27. Mouine S, Yahiaoui I, Verroust-Blondet A (2012) Advanced shape context for plant species identification using leaf image retrieval. In: Proceedings of the 2nd ACM international conference on multimedia retrieval, ICMR ’12, pp 49:1–49:8

  28. Mouine S, Yahiaoui I, Verroust-Blondet A (2013) A shape-based approach for leaf classification using multiscaletriangular representation. In: ICMR

  29. Mzoughi O, Yahiaoui I, Boujemaa N, Zagrouba E (2013) Advanced tree species identification using multiple leaf parts image queries. In: IEEE international conference on image processing (ICIP)

  30. Mzoughi O, Yahiaoui I, Boujemaa N, Zagrouba E (2013) Automated semantic leaf image categorization by geometric analysis. In: ICME

  31. Nanni L, Lumini A, Brahnam S (2012) Survey on {LBP} based texture descriptors for image classification. Expert Syst Appl

    Article  Google Scholar 

  32. Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9:62–66

    Article  Google Scholar 

  33. Prasad S, Kudiri KM, Tripathi RC (2011) Relative sub-image based features for leaf recognition using support vector machine. In: Proceedings of the 2011 international conference on communication, ICCCS ’11, pp 343–346

  34. Rejeb Sfar A, Boujemaa N, Geman D (2013) Identification of plants from multiple images and botanical idkeys. In: Proceedings of the 3rd ACM conference on international conference on multimedia retrieval ICMR

  35. Sfar AR, Boujemaa N, Geman D (2013) Vantage feature frames for fine-grained categorization. In: CVPR. IEEE

  36. Shinji M, Keiichi N, Nobuo E, Hotaka T, Shinji Y (2007) Detection of wilt by analyzing color and stereo vision data of plant. In; MIRAGE’07, pp 400–411

  37. Snelick R, Indovina M, Yen J, Mink A (2003) Multimodal biometrics: Issues in design and testing. In: Proceedings of the 5th international conference on multimodal interfaces, ICMI ’03

  38. Wang J, Bai X, You X, Liu W, Latecki LJ (2012) Shape matching and classification using height functions. Pattern Recogn Lett

    Article  Google Scholar 

  39. Wang Z, Chi Z, Feng D (2003) Shape based leaf image retrieval. VISP, pp 34–43

    Article  Google Scholar 

  40. Wanga XF, Huanga DS, Dua JX, Xua H, Heutted L (2008) Classification of plant leaf images with complicated background. AMC, pp 916–926

    Article  MathSciNet  Google Scholar 

  41. Wu SG, Bao FS, Xu EY, Wang YX, Chang YF, Xiang QL (2007) A leaf recognition algorithm for plant classification using probabilistic neural network. IEEE ISSPIT, pp 11–16

  42. Yahiaoui I, Mzoughi O, Boujemaa N (2012) Leaf shape descriptor for tree species identification. ICME2012

Download references

Author information

Authors and Affiliations

  1. INRIA, Saclay, France

    Olfa Mzoughi, Itheri Yahiaoui & Nozha Boujemaa

  2. SIIVA/RIADI, Intitut Supérieur d’Informatique, Université de Tunis El Manar, Tunis, Tunisia

    Olfa Mzoughi & Ezzeddine Zagrouba

  3. CReSTIC Université de Reims, Champagne-Ardenne, France

    Itheri Yahiaoui

Authors
  1. Olfa Mzoughi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Itheri Yahiaoui
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nozha Boujemaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ezzeddine Zagrouba
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Olfa Mzoughi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mzoughi, O., Yahiaoui, I., Boujemaa, N. et al. Semantic-based automatic structuring of leaf images for advanced plant species identification. Multimed Tools Appl 75, 1615–1646 (2016). https://doi.org/10.1007/s11042-015-2603-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-015-2603-8

Keywords

Search

Navigation