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Shape Matching for Foliage Database Retrieval

Shape Matching for Foliage Database Retrieval

Haibin Ling, David W. Jacobs
Copyright: © 2009 |Pages: 30
ISBN13: 9781605661889|ISBN10: 1605661880|ISBN13 Softcover: 9781616926021|EISBN13: 9781605661896
DOI: 10.4018/978-1-60566-188-9.ch004
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MLA

Ling, Haibin, and David W. Jacobs. "Shape Matching for Foliage Database Retrieval." Semantic Mining Technologies for Multimedia Databases, edited by Dacheng Tao, et al., IGI Global, 2009, pp. 100-129. https://doi.org/10.4018/978-1-60566-188-9.ch004

APA

Ling, H. & Jacobs, D. W. (2009). Shape Matching for Foliage Database Retrieval. In D. Tao, D. Xu, & X. Li (Eds.), Semantic Mining Technologies for Multimedia Databases (pp. 100-129). IGI Global. https://doi.org/10.4018/978-1-60566-188-9.ch004

Chicago

Ling, Haibin, and David W. Jacobs. "Shape Matching for Foliage Database Retrieval." In Semantic Mining Technologies for Multimedia Databases, edited by Dacheng Tao, Dong Xu, and Xuelong Li, 100-129. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-188-9.ch004

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Abstract

Computer-aided foliage image retrieval systems have the potential to dramatically speed up the process of plant species identification. Despite previous research, this problem remains challenging due to the large intra-class variability and inter-class similarity of leaves. This is particularly true when a large number of species are involved. In this chapter, the authors present a shape-based approach, the inner-distance shape context, as a robust and reliable solution. The authors show that this approach naturally captures part structures and is appropriate to the shape of leaves. Furthermore, they show that this approach can be easily extended to include texture information arising from the veins of leaves. They also describe a real electronic field guide system that uses our approach. The effectiveness of the proposed method is demonstrated in experiments on two leaf databases involving more than 100 species and 1,000 leaves.

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