Abstract
Most content-based image retrieval systems use image features such as textures, colors, and shapes. However, in the case of leaf image, it is not appropriate to rely on color or texture features only because such features are similar in most leaves. In this paper, we propose a novel leaf image retrieval scheme which first analyzes leaf venation for leaf categorization and then extracts and utilizes shape feature to find similar ones from the categorized group in the database. The venation of a leaf corresponds to the blood vessel of organisms. Leaf venations are represented using points selected by the curvature scale scope corner detection method on the venation image, and categorized by calculating the density of feature points using non-parametric estimation density. We show its effectiveness by performing several experiments on the prototype system.
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References
Kim, S., Tak, Y., Nam, Y., Hwang, E.: mClover: mobile Content-based Leaf Image Retrieval System. In: ACM Multimedia 2005 (2005)
Sonobe, H., Takagi, S., Yoshimoto, F.: Mobile Computing System for Fish Image Retrieval. In: Proc. of International Workshop on Advanced Image Technology (IWAIT) (poster session), Singapore, January 2004, pp. 33–37 (2004)
Parzen, E.: On Estimation of a Probability Density Function and Mode. Ann. Math. Statist. 33, 1065–1076 (1962)
Sklansky, C., et al.: Minimum perimeter polygons of digitized silhouetts (1972)
Nam, Y., Hwang, E.: A Shape-Based Retrieval Scheme for Leaf Image. In: Ho, Y.-S., Kim, H.-J. (eds.) PCM 2005. LNCS, vol. 3767, pp. 876–887. Springer, Heidelberg (2005)
Im, C., Nishida, H., Kunii, T.L.: Recognizing Plant Species by Normalized Leaf Shapes. In: Vision Interface 1999, Trois-Rivières, Canada, May 19-21, pp. 397–404 (1999)
Wang, Z., Chi, Z., Feng, D., Wang, Q.: Leaf Image Retrieval with Shape Features. In: Laurini, R. (ed.) VISUAL 2000. LNCS, vol. 1929, pp. 477–487. Springer, Heidelberg (2000)
Lee, C.B.: Illustrated flora of Korea. In: Hangmoonsa (1999) ISBN-8971871954
Mokhtarian, F., Suomela, R.: Curvature Scale Scope Based Image Corner Detection. In: Proc. European Signal Processing Conference, Greece, pp. 2549–2552 (1998)
Canny, J.: A Computational Approach to Edge Detection. IEEE Trans. Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)
Alt, H., Behrends, B., Blomer, J.: Approximate matching of polygonal shapes. Ann. Math. Artif. Intell. 13, 251–266 (1995)
Wang, Z., Chi, Z., Feng, D., Wang, Q.: Leaf Image Retrieval with Shape Features. In: Laurini, R. (ed.) VISUAL 2000. LNCS, vol. 1929, pp. 477–487. Springer, Heidelberg (2000)
Mokhtarian, F., Abbasi, S.: Matching Shapes with Self-Intersections: Application to Leaf Classification. IEEE Transactions on Image Processing 13(5), 653–661 (2004)
The MathWorks - MATLAB and Simulink for Technical Computing, http://www.mathworks.com
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Park, JK., Hwang, E., Nam, Y. (2006). A Venation-Based Leaf Image Classification Scheme. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_32
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DOI: https://doi.org/10.1007/11880592_32
Publisher Name: Springer, Berlin, Heidelberg
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