結合邊緣裁切與圖縫裁減暨縮放之影像畫面調整技術

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姓名

吳浩維(Hao-wei Wu) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

結合邊緣裁切與圖縫裁減暨縮放之影像畫面調整技術
(Image Retargeting by Cropping, Seam Carving and Scaling)

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摘要(中)

本研究提出結合多種運算子(multi-operator)的影像重新定位(image retargeting)演算法，數位影像被循序且適當地施予邊緣裁切(cropping)、圖縫裁減(seam carving)與縮放(scaling)等三種方式，達到目標解析度。首先，我們計算影像中的視覺顯著特徵 (visual saliency feature)以作為畫面調整的依據。在邊緣裁切中，擁有較大連通數的前景物體將被擷取，並以其邊緣訂出裁切邊界。圖縫裁減則利用動態規劃方法(dynamic programming)刪除最小能量圖縫，並利用限制刪除圖縫後所產生的局部能量大小決定圖縫裁減停止點。對於某些適合的影像，我們以增加圖縫的方式讓影像長寬比例進一步接近目標長寬比。最後，畫面將直接被縮放至目標大小以在適當的顯示器上呈現影像內容。實驗結果顯示，經由上述簡易的判斷與操作，我們確實能夠維持影像主體，避免在不同長寬比例的影像大小改變下產生嚴重失真，處理後的影像與其他使用較複雜方式所獲得的影像相差無幾，本演算法因而具有較高的實用性。

摘要(英)

A new multi-operator image retargeting approach is proposed in this research. Cropping, seam carving and scaling are applied sequentially on the image to acquire the image with the targeted resolution. The saliency map of the image is first computed to serve as the reference for the subsequent processing. The foreground objects that occupy larger areas will be extracted and the boundaries of objects will be used to determine the edges for cropping. Then, seam carving is applied to remove insignificant content by employing the dynamic programming. The local energy decides when the seam carving process should be stopped. For certain appropriate images, the seams are increased so that the resulting aspect ratio can be approaching the targeted one. Finally, the image is simply scaled to the resolution of the display. The experimental results demonstrate that the essential part the image can be maintained to avoid the serious distortion from the resolution changes. Compared with the images obtained by adopting more complicated methodologies, the image of our scheme is not inferior so the efficiency can be achieved.

關鍵字(中)

★ 多種運算子
★ 影像重新定位
★ 邊緣裁切
★ 圖縫裁減
★ 視覺顯著特徵

關鍵字(英)

★ Multi-Operator
★ Image Retargeting
★ Cropping
★ Seam Carving
★ Visual Saliency Feature

論文目次

中文摘要 i
Abstract ii
誌謝 iii
目錄 iv
附圖目錄 vi
第一章緒論 1
1.1 研究背景與動機 1
1.2 研究貢獻 5
1.3 論文架構 6
第二章相關研究 7
2.1 邊緣裁切方法 7
2.2 影像變形方法 8
2.3 圖縫裁減方法 9
2.4 多種運算子方法 10
第三章提出之方法 12
3.1 系統流程 12
3.2 視覺顯著特徵 13
3.3 邊緣裁切 18
3.3.1 前景提取 18
3.3.2 連通數計算 19
3.3.3 裁切邊緣分析 23
3.4 圖縫裁減 28
3.4.1 圖縫連接的方法 28
3.4.2 空間關聯度衡量 31
3.4.3 圖縫裁減停止點分析 35
3.4.4 圖縫添加 37
3.5 均勻縮放 39
第四章實驗結果 40
4.1 L-VSF顯著圖 40
4.2 邊緣裁切實驗結果 43
4.3 邊緣裁切暨圖縫裁減實驗結果 47
4.4 比較 51
第五章結論與未來方向 63
參考文獻 65

參考文獻

[1] D. Vaquero, M. Turka, K. Pullib, M. Ticob, and N. Gelfandb, "A survey of
image retargeting techniques," Proceedings of SPIE the International Society for Optical Engineering, vol. 7798, p. 779814, 2010.
[2] M. Rubinstein, D. Gutierrez, and O. Sorkine, "A comparative study of image retargeting," ACM Transactions on Graphics (TOG), vol. 29, no. 6, p. 160, 2010.
[3] S. Montabone, and A. Soto. "Human detection using a mobile platform
and novel features derived from a visual saliency mechanism," Image and
Vision Computing, vol. 28, no. 3, pp. 391-402, 2010.
[4] L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence,vol. 20, no. 11, pp. 1254-1259, 1998.
[5] M. Zhang, and L. Zhang, "Auto cropping for digital photographs, " IEEE International Conference on Multimedia and Expo. p. 4-pp, 2005.
[6] F. Stentiford, "Attention based auto image cropping," The 5th International Conference on Computer Vision Systems, Bielefeld, 2007.
[7] I. S. Amrutha, S. S. Shylaja, S. Natarajan, and K. N. Murthy, "A smart automatic thumbnail cropping based on attention driven regions of interest extraction," Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human. ACM, pp. 957-962, 2009.
[8] M. Nishiyama, T. Okabe, Y. Sato, and I. Sato, "Sensation-based photo cropping," Proceedings of the 17th ACM international conference on Multimedia, pp. 669-672, 2009.
[9] P. Cheatle, "Automatic image cropping for republishing," IS&T/SPIE
Electronic Imaging. International Society for Optics and Photonics, pp.
75400O-75400O-9, 2010.
[10] A. Santella , M. Agrawala, D. DeCarlo, D. Salesin, and M. Cohen, "Gaze-based interaction for semi-automatic photo cropping," Proceedings of the SIGCHI conference on Human Factors in computing systems. pp. 771-780, ACM, 2006.
[11] H. Liu, X. Xie, W. Y. Ma, and H. J. Zhang, "Automatic browsing of large
pictures on mobile devices," Proceedings of the eleventh ACM international conference on Multimedia. pp. 148-155, 2003.
[12] B. Suh, H. Ling, B. B. Bederson, and D. W. Jacobjs, "Automatic thumbnail cropping and its effectiveness," Proceedings of the 16th annual ACM symposium on User interface software and technology, 2003.
[13] G. Ciocca, C. Cusano, F. Gasparini, and R. Schettini, "Self-adaptive image cropping for small displays," IEEE Transactions on Consumer Electronics, vol. 53, no. 4, pp. 1622-1627, 2007.
[14] S. Avidan, and A. Shamir. "Seam carving for content-aware image resizing," ACM Transactions on graphics (TOG). vol. 26. no. 3. Aug 2007.
[15] M. Rubinstein, A. Shamir, and S. Avidan, "Improved seam carving for video retargeting," ACM Transactions on Graphics (TOG). vol. 27. no. 3. p. 16, 2008.
[16] M. Grundmann, V. Kwatra, M. Han, and I. Essa, "Discontinuous seam-carving for video retargeting," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, June 2010.
[17] D. Domingues, A. Alahi, and P. Vandergheynst, "Stream carving: an adaptive seam carving algorithm," 17th IEEE International Conference on Image Processing (ICIP), pp. 901-904, 2010.
[18] R. Gal, O. Sorkine, and D. Cohen-Or, "Feature-aware texturing," Proceedings of the 17th Eurographics conference on Rendering Techniques. Eurographics Association, June 2006.
[19] L. Wolf, M. Guttmann, and D. Cohen-Or, "Non-homogeneous content-driven video-retargeting," IEEE 11th International Conference on Computer Vision, 2007. ICCV 2007, 2007.
[20] Y. S. Wang, C. L. Tai, O. Sorkine, and T. Y. Lee, "Optimized scale-and-stretch for image resizing," ACM Transactions on Graphics (TOG), vol. 27, no. 5, 2008.
[21] S. Hua, G. Chen, H. Wei , and Q. Jiang, "Similarity measure for image resizing using SIFT feature," EURASIP Journal on Image and Video Processing , pp. 1-11, Jan 2012.
[22] M. Rubinstein, A. Shamir, and S. Avidan, "Multi-operator media retargeting," ACM Transactions on Graphics (TOG), vol. 28, no. 3, 2009.
[23] W. Dong, N. Zhou, J. C. Paul, and X. Zhang, "Optimized image resizing using seam carving and scaling," ACM Transactions on Graphics (TOG) , vol. 28, no. 5, p125, 2009.
[24] Y. S. Wang, H. C. Lin, O. Sorkine, and T. Y. Lee, "Motion-based video retargeting with optimized crop-and-warp," ACM Transactions on Graphics (TOG) , vol. 29, no. 4, p.90, 2010.
[25] S. Luo, J. Zhang, Q. Zhang, and X. Yuan, "Multi-operator image retargeting with automatic integration of direct and indirect seam carving," Image and Vision Computing, 2012.
[26] W. M. Dong, G. B. Bao, X. P. Zhang, and J. C. Paul, "Fast Multi-Operator Image Resizing and Evaluation," Journal of Computer Science and Technology , vol. 27, no. 1, pp. 121-134, 2012.

指導教授

蘇柏齊(Po-chyi Su)

審核日期

2013-9-25

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