1. 南台科技大學 資訊工程系 An effective solution for trademark image retrieval by combining shape description and feature matching 指導教授：李育強 報告者 ：楊智雁 日期 ： 2010/08/27 Contents lists available at ScienceDirect, Pattern Recognition 43 (2010) 2017–2027

2. 2 Outline Introduction 1 An effective shape description method 2 An effective feature matching strategy 3 Experiments 4 5Conclusion

3. 3 1. Introduction  How to extract appropriate feature vectors to represent image  How to carry out the image retrieval based on the extracted feature vectors effectively  We concentrate on shape- based solution for TIR

4. 4 1. Introduction (c.)  Jain and Vailaya [5] proposed the weight-based solution (WBS)  Wei et al. [6] proposed the two-component solution (TCS)

5. 5 2. An effective shape description method  1. RAPC-HCD  RAPC denotes the relationship among two adjacent boundary points and the centroid  HCD denotes the histogram of centroid distances

6. 6 2.An effective shape description method (c.)

7. 7  2. SDFP-FPM  Among these moment descriptors, Zernike moments are better  But the computation of Zernike moments is very complex

8. 8 2.An effective shape description method (c.)  Feature points matching (FPM)  Spatial distribution of feature points (SDFP)  Which combines the feature points matching and the spatial distribution of feature points to represent the region-based shape feature (SDFP-FPM)

9. 9 2.An effective shape description method (c.)  We use the Kanade– Lucas–Tomasi feature tracker [22] to extract feature points  The final retrieval results are sorted by the descending order of

10. 10 3. An effective feature matching strategy  Two dissimilarity values  Contour-based shape feature (CSF)  Region-based shape feature (RSF)

11. 11 3.An effective feature matching strategy (c.)

12. 12 4. Experiments  Our image database contains 1400 well labeled images

13. 13 5. Conclusion  We address the problem of trademark image retrieval (TIR) by proposing a novel solution  For extracting the contour-based shape feature, we proposed RAPC-HCD descriptor  In future work, we will consider how to further improve the robustness of our shape descriptors in order to apply our solution to other applications in CBIR

14. 南台科技大學 資訊工程系