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RISS 인기검색어
- 검색키워드
- 저자 : Jilong Bian (검색결과 2 건)
- 무료
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- 유료
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A Small Baseline Stereo Matching Method Based on Adaptive Weight
Jilong Bian,Jinfeng Li,Nana Wang,Liu Yang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.9
Due to a high percentage of the bad pixels in small baseline stereo matching method, a small baseline stereo matching method based on adaptive weight is proposed. Firstly, the size of reference window is adaptively calculated for each reference point and then matching costs is evaluated according to adaptive weights and reference window size. Secondly, winner take all is used to evaluate initial disparities and unreliable matches are refused by using reliability constraints. Finally, disparity post processing method based on iterative diffuse using a new cost function is used to obtain a dense disparity map. A small baseline stereo image pair of Toulouse and stereo image pairs provided by the benchmark Middlebury database are used to test the proposed method. The experimental results show that this method can effectively reduce a percentage of the bad pixels of depth discontinuity areas, improve the overall disparity matching accuracy and meet the requirements of small baseline three-dimensional reconstruction.
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RST Invariant Fragile Watermarking for 2D Vector Map Authentication
Nana Wang,Jilong Bian,Han Zhang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.4
2D vector maps are very important data in geographical information systems (GISs). It is considered to be content for which verification of integrity and authentication are urgently required. Using a marking technique and a rotation, scaling and translation (RST) invariant watermark generation method, we propose a scheme that detects and locates malicious attacks with high accuracy while providing the RST invariance property. In particular, we propose setting a unique mark on each feature, calculating the authentication watermark for each spatial feature group by folding the hash results of the differences of the log-radiuses, and embedding the watermark using a RST invariant watermarking method. While the watermark ensures both the sensitivity to malicious manipulations and the RST invariance property, the mark of each feature provides superior accuracy of tamper localization. Moreover, this algorithm is immune to feature rearrangement and vertex reversing operations. Theoretical analysis and experimental results are provided to demonstrate the effectiveness of our method.
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