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Small target detection combining regional stability

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Presentation on theme: "Small target detection combining regional stability"— Presentation transcript:

1 Small target detection combining regional stability
and saliency in a color image Source: Multimedia Tools and Applications, vol. 76, no. 13, pp , Jul Authors: Jing Lou, Wei Zhu, Huan Wang, and Mingwu Ren Speaker: Yu-Wei Nien Date: 5/10/2018

2 Outline Introduction Related works Proposed method
Experimental results Conclusions

3 Introduction (a) Original (b) Result (c) GT (Ground true)
(d) Warning system

4 Related works – MSER-stability (1/3)
200 245 230 60 68 78 250 149 56 29 235 124 222 221 TH= [30 ,200] (a) Original image (b) TH = 30 (c) TH = 80 (d) TH = 200 (e) TH = 201

5 Related works – MSER-stability (2/3)
(a) Original image (b) Gray image (c) Binary image

6 Related works – MSER-stability (3/3)
(a) Original image (b) GT (c) MSER (d) Ours [18] J. Matas, O. chum, M. Urban,and T. Pajdla, “Robust wide-baseline stereo from maximally stable extremal regions,” Image and Vision Computing, vol. 22, no. 10, pp , Sep. 2004

7 Proposed method – Flowchart (1/10)
ρ = 16

8 Proposed method – Regional Stability (RSt) (2/10)
Clustering regions B (2.5, 2.5) C (4.5, 4.5) A (5, 5) TH= 40 TH=24

9 Proposed method – Regional Stability (RSt) (3/10)
(a) Binary image (b) TH= 24 (d) TH= 40

10 Proposed method – Regional Stability (RSt) (4/10)
(b) Sub-image Gr (a) Gray image (d) 𝑀 𝑇 (c) Binary image

11 Proposed method – Regional Stability (RSt) (5/10)
(a) Original image (b) GT (c) 𝑀 𝑇

12 Proposed method – Regional Saliency (RSa) (6/10)
RGB color space -> L*a*b* color space L*= [0, 100] a*= [-128, 127] b*= [-128, 127] Gaussian blurred 64 32 80 1/16 2/16 4/16 4 5 =34

13 Proposed method – Regional Saliency (RSa) (7/10)
(a) Original image 9 6 4 15 7 5 61 3 8 11 44 35 77 17 32 86 83 81 82 72 62 15 68 73 85 66 32 84 42 60 45 77 76 (b) channel 𝐿 (c) channel 𝐿 𝑤 (d) 𝑀 𝐴

14 Proposed method – Regional Saliency (RSa) (8/10)
(a) Original image (b) 𝑀 𝐴

15 Proposed method – Combine (9/10)
1 0.3 0.8 1 0.3 0.8 1 𝑀 𝑇 (a) 𝑀 𝐴 (b) (c) Result 𝑀

16 Proposed method – Combine (10/10)
0.9 0.3 𝑀 𝑇 (a) (c) 𝑀 (d) Result 𝑀 𝐴 (b)

17 Experimental results (1/6)
(a) Original image (b) GT (c) Result

18 Experimental results (2/6)

19 Experimental results (3/6)

20 Experimental results (4/6)
(a) Original image (b) GT (c) AC (d) MSS (e) FT (f) COV (g) HFT (h) GR (i) SUN (j) RBD (k) SR (l) RSa

21 Experimental results (5/6)

22 Experimental results (6/6)
(a) Original image (b) GT (b) Result

23 Conclusions Combining regional stability and saliency Enhance accurate

24 Thanks for Listening


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