Improved Orthogonal T-Snake Model for Complex Water Boundary Extraction

doi:10.11947/j.AGCS.2015.20140404

Abstract

Abstract:

A topology adaptive snake (T-Snake) model based on orthogonal grids is introduced and improved in this paper, and a proper energy function is designed. A detection and handling mechanism for topological conflict that caused by island shaped hollow is proposed in the model, and therefore accurate extraction for complex boundary of river containing river islands is achieved. For the disadvantage of the need to manually construct the initial contour in the orthogonal T-Snake model, using the minimum fractal dimension to obtain one area of the water and automatically generate an initial contour. The experiment shows that the algorithm of this paper can accurately extract the boundary of the complex water which contains deeply concave regions or river islands, and it has higher accuracy and less time cost than classic Snake model and GVF Snake model.

Key words: topology adaptive snake (T-Snake), river island, initial contour, fractal dimension, boundary extraction

CLC Number:

P237

MENG Lingkui, LÜ Qifei. Improved Orthogonal T-Snake Model for Complex Water Boundary Extraction[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6): 670-677.

References

[1] JIANG H, FENG M, ZHU Y, et al. An Automated Method for Extracting Rivers and Lakes from LandSat Imagery[J]. Remote Sensing, 2014, 6(6): 5067-5089.
[2] YANG Shuwen, XUE Chongsheng, LIU Tao, et al. A Method of Small Water Information Automatic Extraction from TM Remote Sensing Images[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(6): 611-617. (杨树文, 薛重生, 刘涛, 等. 一种利用TM影像自动提取细小水体的方法[J]. 测绘学报, 2010, 39(6): 611-617.)
[3] SHEN Li, TANG Hong, WANG Shidong, et al. River Extraction from the High Resolution Remote Sensing Image Based on Spatially Correlated Pixels Template and Adaboost Algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(3): 344-350. (慎利, 唐宏, 王世东, 等. 结合空间像素模板和Adaboost算法的高分辨率遥感影像河流提取[J]. 测绘学报, 2013, 42(3): 344-350.)
[4] KASS M, WITKIN A, TERZOPOULOS D. Snakes: Active Contour Models[J]. International Journal of Computer Vision, 1988, 1(4): 321-331.
[5] WU Liang, HU Yun'an. Balloon Snake with Adjustable Expansion Coefficient in Road Contour Extraction[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(1): 71-77. (吴亮, 胡云安. 膨胀系数可调的Balloon Snake方法在道路轮廓提取中的应用[J]. 测绘学报, 2011, 40(1): 71-77.)
[6] HAN Min, SUN Yang. A Method of Vector Edge Updating Based on Grouping Snake Model in GIS[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(2): 168-174. (韩敏, 孙杨. 一种基于分组式蛇模型的GIS矢量边界更新方法[J]. 测绘学报, 2009, 38(2): 168-174.)
[7] DILLABAUGH C R, NIEMANN K O, RICHARDSON D E. Semi-Automated Extraction of Rivers from Digital Imagery[J]. GeoInformatica, 2002, 6(3): 263-284.
[8] MIAO Lixin, TANG Shouzheng, LI Xia, et al. Extract Reservoir Water Area Automatically Using Masked Active Contour Model from Multispectral Remote Sensing Images[J]. Research of Soil and Water Conservation, 2010, 17(5): 7-11. (苗立新, 唐守正, 李霞,等. 利用掩膜主动轮廓模型提取水库水面面积[J]. 水土保持研究, 2010, 17(5): 7-11.)
[9] XU C Y, PRINCE J L. Snakes, Shapes, and Gradient Vector Flow[J]. IEEE Transactions on Image Processing, 1998, 7(3): 359-369.
[10] HU Qian, ZHANG Feng, LIU Renyi, et al. Land-sea Boundary Extraction Based on Gradient Vector Flow and Active Contour Model[J]. Journal of Zhejiang University: Science Edition, 2013, 40(6): 698-704. (胡倩, 张丰, 刘仁义,等. 基于梯度矢量流和主动轮廓模型的海陆边界提取[J]. 浙江大学学报: 理学版, 2013, 40(6): 698-704.)
[11] SHENG G F, YANG W, DENG X P, et al. Coastline Detection in Synthetic Aperture Radar (SAR) Images by Integrating Watershed Transformation and Controllable Gradient Vector Flow (GVF) Snake Model[J]. IEEE Journal of Oceanic Engineering, 2012, 37(3): 375-383.
[12] ZHU Shulong, MENG Weichan, ZHU Baoshan. Irregular Water Boundary Extraction Using GVF Snake[J]. Journal of Remote Sensing, 2013, 17(4): 742-758. (朱述龙, 孟伟灿, 朱宝山. 运用GVF Snake算法提取水域的不规则边界[J]. 遥感学报, 2013, 17(4): 742-758.)
[13] MCLNERNEY T, TERZOPOULOS D. T-Snakes: Topology Adaptive Snakes[J]. Medical Image Analysis, 2000, 4(2): 73-91.
[14] BISCHOFF S, KOBBELT L P. Snakes with Topology Control [J]. The Visual Computer, 2004, 20(4): 217-228.
[15] SUN Zheng. Coronary Vessel Detection and Motion Tracking Based on T-Snake Model[J]. Journal of Optoelectronics·Laser, 2007, 18(10): 1260-1264. (孙正. 基于T-snake模型的冠状动脉血管提取和运动跟踪[J]. 光电子·激光, 2007, 18(10): 1260-1264.)
[16] ZHOU Jie, JIANG Xiaohua, CHENG Liuquan, et al. Coronary Artery Edge Detection Based on an Orthogonal T-Snake Model[J]. Journal of Tsinghua University: Science and Technology, 2009, 49(1): 41-44. (周洁, 蒋晓华, 程流泉,等. 基于正交T-Snake模型的冠状动脉边缘检测[J]. 清华大学学报: 自然科学版, 2009, 49(1): 41-44.)
[17] ZHENG S. An Intensive Restraint Topology Adaptive Snake Model and Its Application in Tracking Dynamic Image Sequence[J]. Information Sciences, 2010, 180(16): 2940-2959.
[18] SUN F R, LIU Z, LI Y L, et al. Improved T-Snake Model Based Edge Detection of the Coronary Arterial Walls in Intravascular Ultrasound Images[C]//Proceedings of the 3rd International Conference on Bioinformatics and Biomedical Engineering. Beijing, China: IEEE, 2009: 1-4.
[19] DIAO X F, ZHANG X Y, WANG T F, et al. Robust Topology-adaptive Snakes for Medical Ultrasonic Image Segmentation[C]//Proceedings of the 3rd International Conference on Biomedical Engineering and Informatics. Yantai, China: IEEE, 2010: 527-530.
[20] YUAN Yanhong, NI Dong. Segmentation of the Left Ventricle Myocardium in Echocardiography Based on T-Snake Model[J]. Journal of Biomedical Engineering Research, 2013, 32(1): 7-11, 21. (袁艳红, 倪东. 基于T-Snake模型的超声左心室心肌分割方法的研究[J]. 生物医学工程研究, 2013, 32(1): 7-11, 21.)
[21] LIANG B Q, WENG Q H, TONG X H. An Evaluation of Fractal Characteristics of Urban Landscape in Indianapolis, USA, Using Multi-sensor Satellite Images[J]. International Journal of Remote Sensing, 2013, 34(3): 804-823.
[22] YU Zifan, LIN Zongjian. Arithmetic Research of Fractal Dimension with Image Face Based on Fractional Brownian Motion[J]. Geomatics and Information Science of Wuhan University, 2005, 30(2): 161-165. (于子凡, 林宗坚. 基于图像表面积的分形布朗运动分数维算法研究[J]. 武汉大学学报: 信息科学版, 2005, 30(2): 161-165.)
[23] GONZALEZ RC, WOODS RE. Digital Image Processing[M]. New York: John Wiley and Song, 1991.