Pruning and matching scheme for rotation invariant leaf image retrieval

Yoon Sik Tak, Eenjun Hwang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


For efficient content-based image retrieval, diverse visual features such as color, texture, and shape have been widely used. In the case of leaf images, further improvement can be achieved based on the following observations. Most plants have unique shape of leaves that consist of one or more blades. Hence, blade-based matching can be more efficient than whole shape-based matching since the number and shape of blades are very effective to filtering out dissimilar leaves. Guaranteeing rotational invariance is critical for matching accuracy. In this paper, we propose a new shape representation, indexing and matching scheme for leaf image retrieval. For leaf shape representation, we generated a distance curve that is a sequence of distances between the leaf's center and all the contour points. For matching, we developed a blade-based matching algorithm called rotation invariant - partial dynamic time warping (RI-PDTW). To speed up the matching, we suggest two additional techniques: i) priority queue-based pruning of unnecessary blade sequences for rotational invariance, and ii) lower bound-based pruning of unnecessary partial dynamic time warping (PDTW) calculations. We implemented a prototype system on the GEMINI framework [1][2]. Using experimental results, we showed that our scheme achieves excellent performance compared to competitive schemes.

Original languageEnglish
Pages (from-to)280-298
Number of pages19
JournalKSII Transactions on Internet and Information Systems
Issue number6
Publication statusPublished - 2008 Dec


  • Dynamic time warping
  • K-NN
  • Range search
  • Rotation invariance
  • Sequence matching
  • Shape-based image retrieval

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


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