基于数码成像的隧道掌子面地质信息系统研究
|
摘要
论文从研究隧道掌子面地质图像入手,通过数字图像处理技术对隧道掌子面地质图像进行分析和处理,以自动或半自动方式提取出掌子面上岩体层理、节理、断层等结构面信息。对宏观上较为明显的结构面,建立相邻隧道掌子面上各岩层层理、节理、断层等结构面的对应关系,从而根据三维建模技术建立隧道开挖部分的三维地质结构模型,并以此预测掌子面前方未开挖部分的岩体结构等信息。根据对前方未开挖部分的岩体结构的预测,反馈给隧道设计与施工,为实现隧道信息化设计与施工提供了重要的技术支撑。
主要结论和成果如下：
1、通过数字图像处理技术,对隧道掌子面地质图像进行图像预处理、边缘检测和边界提取,对同一结构面上不连续结构面边界采用边界聚合、边界自动连接算法进行连接,提取出的边界可作为地质素描图中的结构面边界,加以少量的人工干预,形成地质素描图,提高了地质素描速度,同时使人工地质素描中因素描人员不同结果也可能极不相同的情况得到有效控制。
2、对于自动边界提取过程中出现实际结构面边界线漏检和误检的情况,加入人工智能剪刀功能。它将图像边界自动提取和人工干预的方式相结合,实现了对结构面边界的半自动提取,既解决了全自动边界提取过程中边界提取错误的情况,也减少了完全手工对结构面边界提取费时、费力且不能精确定位结构面边界的情况。
3、通过数字图像处理技术,从细观上对隧道掌子面岩体特征进行了统计分析,取得岩体结构面长度、单位面积裂隙长度、结构面平均间距、RQD等结构面的自然特征,并据此对掌子面岩体状况进行描述。实现了对隧道掌子面岩体的自动分析和评价功能。
4、对隧道掌子面附近边墙及拱部未衬砌区域的围岩,分析了图像采集时需要注意的问题,研究了生成地质展开图像的算法。
5、通过数字图像处理技术,对近距离拍摄的多种岩石标本的大量岩石图像样本进行特征提取。根据BP神经网络算法,对图像特征参数进行训练,得到参数模型,该模型可用于自动判别不同的隧道掌子面岩体的岩性。
6、根据现场测得的结构面产状信息,对自动建立相邻隧道掌子面上岩体层理、节理、断层等结构面边界线的对应关系进行了探讨。根据OpenGL三维建模技术及三维重建相关算法,建立隧道已开挖部分的三维地质结构模型,实现了隧道地质结构的可视化,从而更加直观的认识隧道开挖部分的地质情况。
7、根据已开挖部分的三维地质结构模型,预测隧道掌子面前方未开挖部分的三维地质结构。由隧道三维地质结构模型及预测模型,生成隧道边墙及拱部的地质展开图、横剖切面、纵剖切面、虚拟地质钻孔等图形,同时利用结构面在大地坐标系下的空间位置关系,分析和计算出各结构面的岩层产状以及结构面走向与隧道开挖方向间的夹角。这些信息有利于全面分析和掌握隧道的地质状况。
8、根据对隧道掌子面的分析,实现了对“隧道掌子面地质信息系统(TFGIS) 2008"的研发,为隧道信息化设计与施工提供了有力的技术支撑。
Starting from studying tunnel face geological images, this paper analyzes and processes tunnel face geological images through digital image processing technology. Structural planes, such as rock mass bedding, joints and faults, are automatically or semi-automatically extracted. For those obvious structural planes, they are corresponded between neighboring faces so that the three-dimensional geological structure model of the tunnel having been excavated part is rebuilt according to three-dimensional modeling technology. From this model, the information of rock mass structures in front of current face is predicted. All this information is given to tunnel design and construction, so as to offer important technical support for realizing tunnel information design and construction.
The main conclusions and achievements are as follows:
1. By using digital imaging technology, face images are pre-processed, edge-detected and boundary-extracted. For a structural plane, if any of its' boundaries are not continuous, boundary polymerization, auto boundary linking algorithm are introduced to connect this discontinuous boundary lines. These boundaries can be regarded as those in geological sketch. Once much manual intervention is applied, the boundary graphs can form geological sketchs. This will improve geological sketch speed. Correspondingly, the situation that manual sketch results are very different because of different sketch operators is efficiently controlled.
2. Considering that undetected and false boundaries are often exist when structural plane boundaries are extracted automatically, manual intelligent scissor which combines auto extracting image boundary with manual intervention is introduced to semi-extracts structural plane boundaries. This method dismisses boundary extraction errors. And it also reduces boundary extraction time, energy, and inaccurate positioning. These cases often exist if completely manual intervention is adopted.
3. Rock masse characters in faces are statistically analyzed by using digital image processing technology. The natural characters of structural planes, such as structural plane length, joint length of unit area, average distance between structural planes, RQD, are acquired. According to these data, the conditions of surrounding rocks in tunnel faces are described. So the function that automatically analyzed and evaluated face surrounding rock conditions is realized.
4. For the surrounding rocks that are adjacent to faces and not laid lining, these questions that need to be cared during image collections are analyzed. And how to produce geological launched maps is researched.
5. By digital image processing technology, characteristic extraction is applied to lots of rock image samples, which are gained through closely shooting many kinds of rocks. According to BP neural network algorithm, image characters are trained so as to obtain parameter model. This model can be used to automatically classify the lithology of different tunnel faces.
6. In accordance with actually measured attitude information of structural planes, how to correspond with structural planes between neighboring faces is discussed. In the light of OpenGL three-dimensional modeling technology and correlatively three-dimensional rebuilding algorithms, the tunnel three-dimensional geological structural model is rebuilt, which means that the visualization of tunnel geological structure is realized. So the geological condition of having being excavated part of tunnel is acquainted more directly.
7. Based on the three-dimensional geological structural model, the unexcavated part in front of current face is predicted. From the predicted model, geological launched map, cross-cutting surface, longitudinal cutting face and virtual geological drilling are built. At the same time, with the special coordinate relation of structural planes in geodetic coordinate system, all structural planes'attitudes and the angle between strike and the direction of tunnel excavation are analyzed and computed. All the information is useful to extensively learn about and analyze tunnel geological conditions.
8. According to the analysis of tunnel faces, "Tunnel Face Geology Information System(TFGIS) 2008" has been developed, which provides strong technical support for tunnel information design and construction.
主要结论和成果如下：
1、通过数字图像处理技术,对隧道掌子面地质图像进行图像预处理、边缘检测和边界提取,对同一结构面上不连续结构面边界采用边界聚合、边界自动连接算法进行连接,提取出的边界可作为地质素描图中的结构面边界,加以少量的人工干预,形成地质素描图,提高了地质素描速度,同时使人工地质素描中因素描人员不同结果也可能极不相同的情况得到有效控制。
2、对于自动边界提取过程中出现实际结构面边界线漏检和误检的情况,加入人工智能剪刀功能。它将图像边界自动提取和人工干预的方式相结合,实现了对结构面边界的半自动提取,既解决了全自动边界提取过程中边界提取错误的情况,也减少了完全手工对结构面边界提取费时、费力且不能精确定位结构面边界的情况。
3、通过数字图像处理技术,从细观上对隧道掌子面岩体特征进行了统计分析,取得岩体结构面长度、单位面积裂隙长度、结构面平均间距、RQD等结构面的自然特征,并据此对掌子面岩体状况进行描述。实现了对隧道掌子面岩体的自动分析和评价功能。
4、对隧道掌子面附近边墙及拱部未衬砌区域的围岩,分析了图像采集时需要注意的问题,研究了生成地质展开图像的算法。
5、通过数字图像处理技术,对近距离拍摄的多种岩石标本的大量岩石图像样本进行特征提取。根据BP神经网络算法,对图像特征参数进行训练,得到参数模型,该模型可用于自动判别不同的隧道掌子面岩体的岩性。
6、根据现场测得的结构面产状信息,对自动建立相邻隧道掌子面上岩体层理、节理、断层等结构面边界线的对应关系进行了探讨。根据OpenGL三维建模技术及三维重建相关算法,建立隧道已开挖部分的三维地质结构模型,实现了隧道地质结构的可视化,从而更加直观的认识隧道开挖部分的地质情况。
7、根据已开挖部分的三维地质结构模型,预测隧道掌子面前方未开挖部分的三维地质结构。由隧道三维地质结构模型及预测模型,生成隧道边墙及拱部的地质展开图、横剖切面、纵剖切面、虚拟地质钻孔等图形,同时利用结构面在大地坐标系下的空间位置关系,分析和计算出各结构面的岩层产状以及结构面走向与隧道开挖方向间的夹角。这些信息有利于全面分析和掌握隧道的地质状况。
8、根据对隧道掌子面的分析,实现了对“隧道掌子面地质信息系统(TFGIS) 2008"的研发,为隧道信息化设计与施工提供了有力的技术支撑。
Starting from studying tunnel face geological images, this paper analyzes and processes tunnel face geological images through digital image processing technology. Structural planes, such as rock mass bedding, joints and faults, are automatically or semi-automatically extracted. For those obvious structural planes, they are corresponded between neighboring faces so that the three-dimensional geological structure model of the tunnel having been excavated part is rebuilt according to three-dimensional modeling technology. From this model, the information of rock mass structures in front of current face is predicted. All this information is given to tunnel design and construction, so as to offer important technical support for realizing tunnel information design and construction.
The main conclusions and achievements are as follows:
1. By using digital imaging technology, face images are pre-processed, edge-detected and boundary-extracted. For a structural plane, if any of its' boundaries are not continuous, boundary polymerization, auto boundary linking algorithm are introduced to connect this discontinuous boundary lines. These boundaries can be regarded as those in geological sketch. Once much manual intervention is applied, the boundary graphs can form geological sketchs. This will improve geological sketch speed. Correspondingly, the situation that manual sketch results are very different because of different sketch operators is efficiently controlled.
2. Considering that undetected and false boundaries are often exist when structural plane boundaries are extracted automatically, manual intelligent scissor which combines auto extracting image boundary with manual intervention is introduced to semi-extracts structural plane boundaries. This method dismisses boundary extraction errors. And it also reduces boundary extraction time, energy, and inaccurate positioning. These cases often exist if completely manual intervention is adopted.
3. Rock masse characters in faces are statistically analyzed by using digital image processing technology. The natural characters of structural planes, such as structural plane length, joint length of unit area, average distance between structural planes, RQD, are acquired. According to these data, the conditions of surrounding rocks in tunnel faces are described. So the function that automatically analyzed and evaluated face surrounding rock conditions is realized.
4. For the surrounding rocks that are adjacent to faces and not laid lining, these questions that need to be cared during image collections are analyzed. And how to produce geological launched maps is researched.
5. By digital image processing technology, characteristic extraction is applied to lots of rock image samples, which are gained through closely shooting many kinds of rocks. According to BP neural network algorithm, image characters are trained so as to obtain parameter model. This model can be used to automatically classify the lithology of different tunnel faces.
6. In accordance with actually measured attitude information of structural planes, how to correspond with structural planes between neighboring faces is discussed. In the light of OpenGL three-dimensional modeling technology and correlatively three-dimensional rebuilding algorithms, the tunnel three-dimensional geological structural model is rebuilt, which means that the visualization of tunnel geological structure is realized. So the geological condition of having being excavated part of tunnel is acquainted more directly.
7. Based on the three-dimensional geological structural model, the unexcavated part in front of current face is predicted. From the predicted model, geological launched map, cross-cutting surface, longitudinal cutting face and virtual geological drilling are built. At the same time, with the special coordinate relation of structural planes in geodetic coordinate system, all structural planes'attitudes and the angle between strike and the direction of tunnel excavation are analyzed and computed. All the information is useful to extensively learn about and analyze tunnel geological conditions.
8. According to the analysis of tunnel faces, "Tunnel Face Geology Information System(TFGIS) 2008" has been developed, which provides strong technical support for tunnel information design and construction.
引文
[1]何发亮,李苍松,陈成宗.隧道地质超前预报[M].成都：西南交通大学出版社.2006.10.
[2]冷彪.数字图像处理在隧道掌子面图像中的研究与实现[D].西南交通大学.2005.4.
[3]刘洋.隧道掌子面图像处理系统的研究与实现[D].西南交通大学.2007.5.
[4]卫洪春.隧道掌子面三维重建、预测的设计与实现[D].西南交通大学.2007.5.
[5]冷彪,仇文革.数字图像处理技术在隧道掌子面的应用[J].岩土力学.2006.10.27：385-388.
[6]Leng Biao, Qiu Wen-ge. Application of digital image processing in tunnel excavation[C]. Proceedings of the 33rd ITA-AITES World Tunnel Congress-Underground Space-The 4th Dimension of Metropolises.2007:553-557.
[7]Kenneth R. Castleman. Digital Image Processing[M]. Publishing House of Electronics Industry.2002.
[8]郎锐.数字图像处理学[M].北京希望电子出版社.2002.
[9]Richard S. Wright, Jr. Michael Sweet著.潇湘工作室译.OpenGL超级宝典(第二版)[M],人民邮电出版社,2001.
[10]关宝树.隧道工程施工要点集[M].人民交通出版社.2003.1.25-32.
[11]Sou-Sen LeuT, Shiu-Lin Chang. Digital image processing based approach for tunnel excavation faces[J]. Automation in Construction.2005,14:750-765.
[12]叶英,王梦恕.隧道掌子面地质信息数字编录识别技术研究[J].北京交通大学学报.2007.2,31(1)：59-62.
[13]周春霖,朱合华,李晓军.新奥法施工隧道掌子面红外照相及图像处理[J].岩石力学与工程学报.2008.6,27(增1)：3166-3172.
[14]秦英译.基于数字钻孔摄像的图像分析方法研究[D].硕士学位论文.武汉：中国科学院研究生院.2006.5.
[15]庞智成.基于高精度数字钻孔图像的岩体不连续面分析方法研究[D]. 硕士学位论文.武汉：中国科学院研究生院.2007.5.
[16]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统[J].岩土工程界.2001,4(12).
[17]葛修润,王川婴.数字全景钻孔摄像技术与数字钻孔[J].地下空间.2001.12,21(4)：254-261.
[18]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统及应用[J].岩土力学.2001.12,22(4)：522-525.
[19]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统研究[J].岩石力学与工程学报.2002.3,21(3)：398-403.
[20]王川婴,LAW K Tim.钻孔摄像技术的发展与现状[J].岩石力学与工程学报.2005.10,24(19)：3440-3448.
[21]杨林.数字影像地质编录系统的研究与开发[D].硕士学位论文.南京：河海大学.2003.3.
[22]杨朝辉,李浩.洞室数字正射影像展示图的生成[J].测绘信息与工程.2003.6,28(3)：16-18.
[23]李浩,张友静,华锡生等.硐室数字摄影地质编录及其基本算法研究[J].武汉大学学报信息科学版.2004.9,29(9)：805-808.
[24]王明华,李浩,苍桂华.普通数码相机在洞室地质编录中的应用[J].煤田地质与勘探.2007.8,35(4)：15-19.
[25]张友静,李浩,吴继敏.基于数码相机的施工地质编录要素提取方法研究[J].工程地质计算机应用.2001,2：15-18.
[26]高改萍,阎利,杨岚等.摄影测量在洞室围岩地质编录成图中的应用[J].人民长江.2002.6,33(6)：54-56.
[27]刘剑,黄东军.数字图像处理技术在工程地质编录中的应用[J].企业技术开发.2004.9,23(9)：6-8.
[28]刘大刚.数码摄影技术在隧道位移信息采集中的研究与应用[D].硕士学位论文.成都：西南交通大学.2004.7.
[29]刘大刚,王明年.数码摄影技术在隧道位移信息采集中的应用[J].地下空间.2004.9,24(3)：336-345.
[30]贾刘强.数字图像处理技术在隧道围岩收敛量测中应用的初步研究[D].硕士学位论文.成都：西南交通大学.2005.3.
[31]贾刘强,王志杰,邱健等.数字图像处理技术在隧道围岩收敛量测中应用的初步研究[J].现代隧道技术.2006.8,43(4)：5-11.
[32]费璟昊,李俊杰,李辉等.利用图像处理实现隧洞断面测量[J].测绘通报.2002,1：21-22.
[33]费璟昊.隧洞断面数字图像处理方法研究及软件开发[D].硕士学位论文.大连理工大学.2001.6.11.
[34]魏继红,吴继敏,孙少锐.图像处理技术在隧洞超欠挖评价中的应用[J].水文地质工程地质.2005,(1)：105-108.
[35]李鹏.基于图像处理的隧道检测[D].硕士学位论文.北京交通大学.2006.12.
[36]张世卓,泰典,林铭郎.影像展开与嵌接技术在隧道检测之应用[J].地下空间与工程学报.2008.8,4(4)：670-675.
[37]S. Noda, K. Ueda. Fire Detection in Tunnels using an Image Processing Method[C]. Vehicle Navigation & Information Systems Conference Proceedings. 1994.57-62.
[38]全洪渊,黄席抛,刘爱君.一种应用于隧道视频监控的图像识别系统[J].安防科技.2007.5.58-61.
[39]T.R. Reid, J.P. Harrison. A semi-automated methodology for discontinuity trace detection in digital images of rock mass exposures[J]. International Journal of Rock Mechanics & Mining Sciences.2000, (37):1073-1089.
[40]D. Deb, S. Hariharan, U.M. Rao, Chang-Ha Ryu. Automatic detection and analysis of discontinuity geometry of rock mass from digital images. Computers & Geosciences[J].2008, (34):115-126.
[41]F. Lemy, J. Hadjigeorgiou. Discontinuity trace map construction using photographs of rock exposures[J].2003, (40):903-917.
[42]郭树棠.利用图像分析的岩层自动评价系统.现代隧道技术.1994.(12).67.
[43]范留明,李宁.基于模式识别技术岩体裂隙图像的智能解译方法研究[J].自然科学进展.2004.2,14(2)：236-240.
[44]范留明,李宁.基于数码摄影技术的岩体裂隙测量方法初探[J].岩石力学与工程学报.2005.3,24(5)：792-797.
[45]王卫星,段姣.基于数宇图像处理技术的岩石节理宽度测量[J].微型计算机与应用.2005,10：51-52.
[46]Weixing Wang, Haijun Liao, Ying Huang. Rock fracture tracing based on image processing and SVM[C]. Third International Conference on Natural Computation.2007.
[47]Weixing Wang, Lei Li. Image Analysis of Multiple Rock Fractures[C]. Proceedings of the IEEE International Conference on Mechatronics & Automation.2005:1272-1276.
[48]Weixing Wang. An edge based segmentation algorithm for rock fracture tracing[C]. Proceeding of the Computer Graphics, Imaging and Vision:New Trend.2005.
[49]崔冰,王卫星.基于统计模式识别的岩石节理图像分割方法[J].计算机工程与应用.2006.10：213-215.
[50]Bing Cui, Weixing Wang and Ling Gan. Complicated Rock Joints Geometry Complexity Analysis Based on Image Processing[C]. Proceedings of the 6th World Congress on Intelligent Control and Automation.2006:9523-9527.
[51]李锐,金文标.岩石节理二值图像的细化[J].微计算机信息.2007,23(2-3)：294-296.
[52]胡刚,金乾坤.岩体天然裂隙计算机图像处理技术研究[J].有色金属.2004.9,56(5)：39-40.
[53]姚骏屏,王卫星.一种基于图像融合的岩石裂隙充填物分割方法[J].重庆邮电学院学报(自然科学版).2006.2,18(1)：82-85.
[54]陆兆溱.工程地质学(第二版)[M].中国水得水电出版社.1998.6.
[55]Yuliana Susilowati, Hari Rahyuwibowo, Tati Richard Mengko. Character-istic of Interference Color in Rock Forming Mineral Images[J]. Digital Object Identifier.2002.10,2(28-31):265-268.
[56]Tati Richard Mengko, Yuliana Susilowati, Richard Mengko. Digital Image Processing Technique in Rock Forming Minerals Identification[J]. Digital Object Identifier.2000.11:441-444.
[57]Imran Sarwar Bajwa. A Study for Prediction of Minerals in Rock Images using Back Propagation Neural Networks[J]. Digital Object Identifier.2006.9: 185-189.
[58]李兵,凌其聪,鲍征宇等.用数字化图像分析法确定岩石物性[J].新疆石油地质.2008.4,29(2)：253-255.
[59]Leng Biao, Qiu Wen-ge, LiuYang etc. Tunnel Three-Dimensional Modeling Research Based on Digital Image Processing[C]. Computer Science and Software Engineering,2008 International Conference.2008.12:887-890.
[60]杜诚,王丹,冷彪等.基于OpenGL的图像三维重建[J].计算机与信息技术.2009.1：44-45.
[61]高华,蒋红斐,张嘉峻.基于OpenGL的隧道三维建模[J].中南公路工程.2007.6.32(3)：137-139.
[62]金淼,赵永辉,谢雄耀.基于OpenGL的隧道监测数据三维可视化表达[J].现代隧道技术.2006(增)：163-166.
[63]金淼,赵永辉,吴健生等.隧道三维可视化监测系统的研制与开发[J].计算机工程.2007.11,33(22)：255-257.
[64]谢小玲,苏海东,陈琴.穿黄隧洞预应力衬砌结构三维非线性有限元分析[J].人民长江.2008.12,39(24)：6-7.
[65]张洵安,王显彬.软岩隧道开挖与支护的三维有限元仿真分析[J].郑州大学学报(工学版).2008.6,29(2)：137-140.
[66]赵伟强,阮永芬,王东.三维数值模型分析白龙边坡的稳定性[J].2009,(1)：134-135.
[67]李新星,朱合华,蔡永昌.基于三维地质模型的岩土工程有限元自动建模方法[J].岩土工程学报.2008.6.30(6)：856-862.
[68]张有天,周维垣.岩石高边坡的变形与稳定[M].北京：中国水得水电出版社.1999.
[69]柴贺军,黄地龙,黄润秋.地质结构面三维扩展模型研究[J].地质灾害与环境保护.1999.10(2)：73-76.
[70]陈昌彦,张菊明,杜永康等.边坡工程地质信息的三维可视化及其在三峡船闸边坡工程中的应用[J].岩土工程学报.1998,20(4)：1-6.
[71]何满潮,刘斌,徐能雄.工程岩体三维可视化构模系统的开发[J].中国矿业大学学报.2003,32(1)：38-43.
[72]杨淑莹.基于断层图像三维重建的体视化技术研究与应用[D].硕士学位论文.天津师范大学.2001.5.
[73]柴贺军.黄地龙.黄润秋.岩体结构面计算机三维扩展模型研究[J].地质灾害与环境保护.1999.6,10(2)：73-76.
[74]贾洪彪,马淑芝,唐辉明.岩体结构面网络三维模拟的工程应用研究[J].岩石力学与工程学报.2002.7,21(7)：976-979.
[75]李志康,许世银.岩体结构三维可视化技术[C].全国矿山建设学术会议论文集.2003：793-797.
[76]韦宏鹄,王建锋,杨玮.岩体中复杂构造的三维可视化方法[C].第二届全国岩土与工程学术大会论文集.2006.10：3-7.
[77]钟登华,李明超,杨建敏.复杂工程岩体结构三维可视化构造及其应用[J].岩石力学与工程学报.2005.2,24(4)：575-580.
[78]陈俊智,侯克鹏,杨继清.关于岩体三维建模的研究[J].云南冶金.2004.10,33(5)：3-6.
[79]杜景灿,陈祖煜,周家骢.节理岩体二维和三维连通特性的对比分析[J].岩石力学与工程学报.2004.6,23(11)：1824-1831.
[80]汪斌,唐辉明,简文星.结构面三维网络模拟在岩体质量评价中的应用[J].岩土力学.2006.4,27(4)：594-596.
[81]李新强,汪小刚,陈祖煌.裂隙岩体三维节理网络的生成和可视化系统研发[C].中国水利学会第四届青年科技论坛论文集.2008.10：435-438.
[82]Mark J. Three-dimensional geological modeling of potential-field data[J]. Computer & Geosciences.2001,27(4):455-465.
[83]Dobson J E. Commentary:A Conceptual framework for integrating remote sensing[J]. GIS and Geography.1993,59(10):1491-1496.
[84]Molenaar M. A topology for 3D vector maps[J]. ITC Journal.1992, (1): 25-33.
[85]Arnaud de la Losa, Bernard C.3D Topological modeling and visualization for 3D GIS[J]. Computers & Graphics.1999, (23):469-478.
[86]Ross R M, Scott E J. Three-dimensional reconstruction and modeling of complexly folded surfaces using Mathematica[J]. Computer & Geosciences. 2001,27(4):401-418.
[87]Lees J M. Xmap8:Three-dimensional GIS for geology and geophysics[J]. Seismological Research Letters.1995,66(4):33-37.
[88]Lees J M., Geotouch. Software for three and four dimensional GIS in earth sciences[J]. Computer & Geosciences.2000,26(7):751-761.
[89]徐能雄.工程岩体三维构模技术及其可视化系统研究[D].北京：中国矿业大学(北京校区).2002.
[90]徐能雄,何满朝.层状岩体三维构模方法与空间数据模型[J].中国矿业大学学报.2004.1,33(1)：103-108.
[91]何满潮,李学元,刘斌等.非层状岩体三维可视化构模技术研究[J].岩石力学与工程学报.2005.3,24(5)：774-779.
[92]徐能雄,田红,于沭.适于岩体结构三维建模的非连续地层界面整体重构[J].岩土工程学报.2007.9,29(9)：1361-1366.
[93]徐能雄,何满潮,景海河.岩体结构三维构模技术及其可视化系统研制[J].岩土工程学.2004.5,26(3)：373-377.
[94]徐能雄,何满潮.褶皱岩体三维可视化构模技术及其工程应用[J].岩土工程学.2003.7,25(4)：418-421.
[95]王笑海.基于三维拓扑格网结构的GIS地层模型研究[D].北京：中国科学院武汉岩土力学所.1999.
[96]贺怀建,白世伟,赵新华等.三维地层模型中地层划分的探讨[J].岩土力学.2001,23(5)：637-639.
[97]陈键.三维地层信息系统的建模与分析研究[D].北京：中国科学院武汉岩土力学所.2001.
[98]Jose Manuel, Vacas Pena. A program in Pascal to simulate the superposition of two or three fold systems[J]. Computer & Geosciences,2002,26(3):341-349.
[99]Zhou ZHAO, En-ke HOU, Zhi-hua ZHANG, Nian-dong DENG. Three dimensional Geological Modeling from Component-based Topological Data Model[J]. International Conference on Computer Modeling and Simulation. 2009.1:43-46.
[100]王李管,尚晓明,曾庆田.三维可视化建模技术在岩体质量评价中的应用[J].岩石力学与工程学报.2008.9,27(增2)：3655-3660.
[101]苏雨涛,李彦生,韩景芸.CT数据三维重建及可视化技术的研究[J].机械设计与制造.2009.1,(1)：191-193.
[102]徐乃平.基于断层图像序列的医学三维图像重建[D].硕士学位论文.天津师范大学.2002.3.
[103]金朝阳.医学图像三维重建及其应用[D].硕士学位论文.浙江大学.2002.6.
[104]许斌,张森,厉万庆.从序列切片重构三维对象的新方法[J].计算机学报.1994.1,17(1)：64-72.
[105]孔宪立主编.工程地质学[M].中国建筑工业出版社.1997.6.
[106]孙家齐.工程地质[M].
[107]章毓晋.图象工程(上册)：图像处理和分析[M].北京：清华大学出版社.1999.3.
[108]李弼程,彭天强,彭波等编著.智能图像处理技术[M].电子工业出版社.2004.7.
[109]Canny J F. A computational approach to edge detection[J]. IEEE Trans on PAMI,1986,8(6):679-698.
[110]Meer P, Georgescu B. Edge detection with embedded confidence[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(12): 1351-1365.
[111]万力,易昂,傅明.一种基于Canny算法的边缘提取改善方法[J].计算机技术与自动化.2003,22(1)：24-26.
[112]崔屹.图像处理与分析—数学形态学方法及应用[M].科学出版社.2000.
[113]唐常青,吕宏伯,黄铮,张方编蓍.数学形态学方法及其应用[M].科学出版社.1990.8.
[114]Eric N. Mortensen, William A. Barrett. Intelligent Scissors for Image Composition[J]. Computer Graphics.1995.8:191-198.
[115]汪斌,唐辉明,简文星等.结构面三维网络模拟在岩体质量评价中的应用[J].岩土力学.2006.4,27(4)：594-596.
[116]边肇祺,张学工.模式识别[M].清华大学出版社.2000.
[117]肖健华编著.智能模式识别方法[M].华南理工大学出版社.2005.9.
[118]谢承泮.神经网络发展综述[J].科技情报开发与经济.2006,16(12)：148-150.
[119]周志华,曹存根主编.神经网络及其应用[M].清华大学出版社.
[120]李学桥,马莉.神经网络.工程应用[M].重庆大学出版社.1996.
[121]胡守仁,余少波,戴葵.神经网络导论[M].国防科技大学出版社.1993.10.
[122]S. Grgic, M. Grgic, and M. Mrak. Reliability of Objective Picture Quality Measures Measurement[J]. Journal of Electrical Engineering.2004,55(1-2): 3-10.
[123]R. Hecht-Nielsen. Theory of Back-propagation Neural Networks[C]. Proceedings of the International Joint Conference on Neural Networks.1989,1: 593-605.
[124]张宏林.Visual C++数字图像模式识别技术及工程实践[M].人民邮电出版社.2003.2
[125]四维科技,胡小锋,赵辉编著.Visual C++/MATLAB图像处理与识别实用案例精选[M].人民邮电出版社.2004.9.
[126]高大启.有教师的线性基本函数前向三层神经网络结构研究[J].计算机学报.1998,21(1)：80-86.
[127]《数学手册》编写组.数学手册[M].高等教育出版社.2004.3.
[128]陈春萍.基于OpenGL的隧道掌子面三维重建系统的设计与实现[D].西南交通大学.2005.4.
[129]苏安,冉蜀阳,吴章文等.基于相邻层轮廓线几何形状匹配的三维重建[J].计算机应用.2009.2,29(2)：451-452.
[130]TAKASAKI H. Moire topography[J]. Appl. Opt,1970,9(9):1467-1472.
[131]G CONG, B PARVIN. An Algebraic Solution to Surface Recovery from Cross-Sectional Contours[J]. Graphical Models and Image Processing.1999, 61(4):222-243.
[132]S H LEE, D GAHN, D Y YANG. Surface reconstruction for mid-slice generation on variable lamination manufacturing[J]. Journal of Materials Processing Technology.2002,130-131:384-389.
[133]邵世禄.截头圆柱面展开图曲线方程的研究[J].甘肃农业大学学报.2002.6,37(2)：260-264.
[134]David J.Kruglinski等著.希望图书创作室译.Programming Visual C++技术内幕6.0(第五版)[M].北京希望电子出版社.1999.
[135]周长发.精通Visual C++图像编程(第三版)[M].电子工业出版社.2000.
[136]孙鑫,余安萍编著.VC++深入详解[M].北京：电子工业出版社.2007.3.
[137]明日科技,宋坤,刘锐宁等编著.Visual C++开发技术大全[M].人民邮电出版社.2007.3.
[138]孙家广等编著.计算机图形学(第三版)[M].清华大学出版社.
[139]飞思科技产品研发中心.SQL Server 2000基础与提高[M].电子工业出版社.2001.7.
[140]武洪萍、马桂婷.数据库原理及应用(SQL Server版)[M].北京大学出版社.2008.2.
[141]启明工作室编著.Visual C++ + SQL Server数据库应用实例完全解析[M].人民邮电出版社.2006.4.
[2]冷彪.数字图像处理在隧道掌子面图像中的研究与实现[D].西南交通大学.2005.4.
[3]刘洋.隧道掌子面图像处理系统的研究与实现[D].西南交通大学.2007.5.
[4]卫洪春.隧道掌子面三维重建、预测的设计与实现[D].西南交通大学.2007.5.
[5]冷彪,仇文革.数字图像处理技术在隧道掌子面的应用[J].岩土力学.2006.10.27：385-388.
[6]Leng Biao, Qiu Wen-ge. Application of digital image processing in tunnel excavation[C]. Proceedings of the 33rd ITA-AITES World Tunnel Congress-Underground Space-The 4th Dimension of Metropolises.2007:553-557.
[7]Kenneth R. Castleman. Digital Image Processing[M]. Publishing House of Electronics Industry.2002.
[8]郎锐.数字图像处理学[M].北京希望电子出版社.2002.
[9]Richard S. Wright, Jr. Michael Sweet著.潇湘工作室译.OpenGL超级宝典(第二版)[M],人民邮电出版社,2001.
[10]关宝树.隧道工程施工要点集[M].人民交通出版社.2003.1.25-32.
[11]Sou-Sen LeuT, Shiu-Lin Chang. Digital image processing based approach for tunnel excavation faces[J]. Automation in Construction.2005,14:750-765.
[12]叶英,王梦恕.隧道掌子面地质信息数字编录识别技术研究[J].北京交通大学学报.2007.2,31(1)：59-62.
[13]周春霖,朱合华,李晓军.新奥法施工隧道掌子面红外照相及图像处理[J].岩石力学与工程学报.2008.6,27(增1)：3166-3172.
[14]秦英译.基于数字钻孔摄像的图像分析方法研究[D].硕士学位论文.武汉：中国科学院研究生院.2006.5.
[15]庞智成.基于高精度数字钻孔图像的岩体不连续面分析方法研究[D]. 硕士学位论文.武汉：中国科学院研究生院.2007.5.
[16]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统[J].岩土工程界.2001,4(12).
[17]葛修润,王川婴.数字全景钻孔摄像技术与数字钻孔[J].地下空间.2001.12,21(4)：254-261.
[18]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统及应用[J].岩土力学.2001.12,22(4)：522-525.
[19]王川婴,葛修润,白世伟.数字式全景钻孔摄像系统研究[J].岩石力学与工程学报.2002.3,21(3)：398-403.
[20]王川婴,LAW K Tim.钻孔摄像技术的发展与现状[J].岩石力学与工程学报.2005.10,24(19)：3440-3448.
[21]杨林.数字影像地质编录系统的研究与开发[D].硕士学位论文.南京：河海大学.2003.3.
[22]杨朝辉,李浩.洞室数字正射影像展示图的生成[J].测绘信息与工程.2003.6,28(3)：16-18.
[23]李浩,张友静,华锡生等.硐室数字摄影地质编录及其基本算法研究[J].武汉大学学报信息科学版.2004.9,29(9)：805-808.
[24]王明华,李浩,苍桂华.普通数码相机在洞室地质编录中的应用[J].煤田地质与勘探.2007.8,35(4)：15-19.
[25]张友静,李浩,吴继敏.基于数码相机的施工地质编录要素提取方法研究[J].工程地质计算机应用.2001,2：15-18.
[26]高改萍,阎利,杨岚等.摄影测量在洞室围岩地质编录成图中的应用[J].人民长江.2002.6,33(6)：54-56.
[27]刘剑,黄东军.数字图像处理技术在工程地质编录中的应用[J].企业技术开发.2004.9,23(9)：6-8.
[28]刘大刚.数码摄影技术在隧道位移信息采集中的研究与应用[D].硕士学位论文.成都：西南交通大学.2004.7.
[29]刘大刚,王明年.数码摄影技术在隧道位移信息采集中的应用[J].地下空间.2004.9,24(3)：336-345.
[30]贾刘强.数字图像处理技术在隧道围岩收敛量测中应用的初步研究[D].硕士学位论文.成都：西南交通大学.2005.3.
[31]贾刘强,王志杰,邱健等.数字图像处理技术在隧道围岩收敛量测中应用的初步研究[J].现代隧道技术.2006.8,43(4)：5-11.
[32]费璟昊,李俊杰,李辉等.利用图像处理实现隧洞断面测量[J].测绘通报.2002,1：21-22.
[33]费璟昊.隧洞断面数字图像处理方法研究及软件开发[D].硕士学位论文.大连理工大学.2001.6.11.
[34]魏继红,吴继敏,孙少锐.图像处理技术在隧洞超欠挖评价中的应用[J].水文地质工程地质.2005,(1)：105-108.
[35]李鹏.基于图像处理的隧道检测[D].硕士学位论文.北京交通大学.2006.12.
[36]张世卓,泰典,林铭郎.影像展开与嵌接技术在隧道检测之应用[J].地下空间与工程学报.2008.8,4(4)：670-675.
[37]S. Noda, K. Ueda. Fire Detection in Tunnels using an Image Processing Method[C]. Vehicle Navigation & Information Systems Conference Proceedings. 1994.57-62.
[38]全洪渊,黄席抛,刘爱君.一种应用于隧道视频监控的图像识别系统[J].安防科技.2007.5.58-61.
[39]T.R. Reid, J.P. Harrison. A semi-automated methodology for discontinuity trace detection in digital images of rock mass exposures[J]. International Journal of Rock Mechanics & Mining Sciences.2000, (37):1073-1089.
[40]D. Deb, S. Hariharan, U.M. Rao, Chang-Ha Ryu. Automatic detection and analysis of discontinuity geometry of rock mass from digital images. Computers & Geosciences[J].2008, (34):115-126.
[41]F. Lemy, J. Hadjigeorgiou. Discontinuity trace map construction using photographs of rock exposures[J].2003, (40):903-917.
[42]郭树棠.利用图像分析的岩层自动评价系统.现代隧道技术.1994.(12).67.
[43]范留明,李宁.基于模式识别技术岩体裂隙图像的智能解译方法研究[J].自然科学进展.2004.2,14(2)：236-240.
[44]范留明,李宁.基于数码摄影技术的岩体裂隙测量方法初探[J].岩石力学与工程学报.2005.3,24(5)：792-797.
[45]王卫星,段姣.基于数宇图像处理技术的岩石节理宽度测量[J].微型计算机与应用.2005,10：51-52.
[46]Weixing Wang, Haijun Liao, Ying Huang. Rock fracture tracing based on image processing and SVM[C]. Third International Conference on Natural Computation.2007.
[47]Weixing Wang, Lei Li. Image Analysis of Multiple Rock Fractures[C]. Proceedings of the IEEE International Conference on Mechatronics & Automation.2005:1272-1276.
[48]Weixing Wang. An edge based segmentation algorithm for rock fracture tracing[C]. Proceeding of the Computer Graphics, Imaging and Vision:New Trend.2005.
[49]崔冰,王卫星.基于统计模式识别的岩石节理图像分割方法[J].计算机工程与应用.2006.10：213-215.
[50]Bing Cui, Weixing Wang and Ling Gan. Complicated Rock Joints Geometry Complexity Analysis Based on Image Processing[C]. Proceedings of the 6th World Congress on Intelligent Control and Automation.2006:9523-9527.
[51]李锐,金文标.岩石节理二值图像的细化[J].微计算机信息.2007,23(2-3)：294-296.
[52]胡刚,金乾坤.岩体天然裂隙计算机图像处理技术研究[J].有色金属.2004.9,56(5)：39-40.
[53]姚骏屏,王卫星.一种基于图像融合的岩石裂隙充填物分割方法[J].重庆邮电学院学报(自然科学版).2006.2,18(1)：82-85.
[54]陆兆溱.工程地质学(第二版)[M].中国水得水电出版社.1998.6.
[55]Yuliana Susilowati, Hari Rahyuwibowo, Tati Richard Mengko. Character-istic of Interference Color in Rock Forming Mineral Images[J]. Digital Object Identifier.2002.10,2(28-31):265-268.
[56]Tati Richard Mengko, Yuliana Susilowati, Richard Mengko. Digital Image Processing Technique in Rock Forming Minerals Identification[J]. Digital Object Identifier.2000.11:441-444.
[57]Imran Sarwar Bajwa. A Study for Prediction of Minerals in Rock Images using Back Propagation Neural Networks[J]. Digital Object Identifier.2006.9: 185-189.
[58]李兵,凌其聪,鲍征宇等.用数字化图像分析法确定岩石物性[J].新疆石油地质.2008.4,29(2)：253-255.
[59]Leng Biao, Qiu Wen-ge, LiuYang etc. Tunnel Three-Dimensional Modeling Research Based on Digital Image Processing[C]. Computer Science and Software Engineering,2008 International Conference.2008.12:887-890.
[60]杜诚,王丹,冷彪等.基于OpenGL的图像三维重建[J].计算机与信息技术.2009.1：44-45.
[61]高华,蒋红斐,张嘉峻.基于OpenGL的隧道三维建模[J].中南公路工程.2007.6.32(3)：137-139.
[62]金淼,赵永辉,谢雄耀.基于OpenGL的隧道监测数据三维可视化表达[J].现代隧道技术.2006(增)：163-166.
[63]金淼,赵永辉,吴健生等.隧道三维可视化监测系统的研制与开发[J].计算机工程.2007.11,33(22)：255-257.
[64]谢小玲,苏海东,陈琴.穿黄隧洞预应力衬砌结构三维非线性有限元分析[J].人民长江.2008.12,39(24)：6-7.
[65]张洵安,王显彬.软岩隧道开挖与支护的三维有限元仿真分析[J].郑州大学学报(工学版).2008.6,29(2)：137-140.
[66]赵伟强,阮永芬,王东.三维数值模型分析白龙边坡的稳定性[J].2009,(1)：134-135.
[67]李新星,朱合华,蔡永昌.基于三维地质模型的岩土工程有限元自动建模方法[J].岩土工程学报.2008.6.30(6)：856-862.
[68]张有天,周维垣.岩石高边坡的变形与稳定[M].北京：中国水得水电出版社.1999.
[69]柴贺军,黄地龙,黄润秋.地质结构面三维扩展模型研究[J].地质灾害与环境保护.1999.10(2)：73-76.
[70]陈昌彦,张菊明,杜永康等.边坡工程地质信息的三维可视化及其在三峡船闸边坡工程中的应用[J].岩土工程学报.1998,20(4)：1-6.
[71]何满潮,刘斌,徐能雄.工程岩体三维可视化构模系统的开发[J].中国矿业大学学报.2003,32(1)：38-43.
[72]杨淑莹.基于断层图像三维重建的体视化技术研究与应用[D].硕士学位论文.天津师范大学.2001.5.
[73]柴贺军.黄地龙.黄润秋.岩体结构面计算机三维扩展模型研究[J].地质灾害与环境保护.1999.6,10(2)：73-76.
[74]贾洪彪,马淑芝,唐辉明.岩体结构面网络三维模拟的工程应用研究[J].岩石力学与工程学报.2002.7,21(7)：976-979.
[75]李志康,许世银.岩体结构三维可视化技术[C].全国矿山建设学术会议论文集.2003：793-797.
[76]韦宏鹄,王建锋,杨玮.岩体中复杂构造的三维可视化方法[C].第二届全国岩土与工程学术大会论文集.2006.10：3-7.
[77]钟登华,李明超,杨建敏.复杂工程岩体结构三维可视化构造及其应用[J].岩石力学与工程学报.2005.2,24(4)：575-580.
[78]陈俊智,侯克鹏,杨继清.关于岩体三维建模的研究[J].云南冶金.2004.10,33(5)：3-6.
[79]杜景灿,陈祖煜,周家骢.节理岩体二维和三维连通特性的对比分析[J].岩石力学与工程学报.2004.6,23(11)：1824-1831.
[80]汪斌,唐辉明,简文星.结构面三维网络模拟在岩体质量评价中的应用[J].岩土力学.2006.4,27(4)：594-596.
[81]李新强,汪小刚,陈祖煌.裂隙岩体三维节理网络的生成和可视化系统研发[C].中国水利学会第四届青年科技论坛论文集.2008.10：435-438.
[82]Mark J. Three-dimensional geological modeling of potential-field data[J]. Computer & Geosciences.2001,27(4):455-465.
[83]Dobson J E. Commentary:A Conceptual framework for integrating remote sensing[J]. GIS and Geography.1993,59(10):1491-1496.
[84]Molenaar M. A topology for 3D vector maps[J]. ITC Journal.1992, (1): 25-33.
[85]Arnaud de la Losa, Bernard C.3D Topological modeling and visualization for 3D GIS[J]. Computers & Graphics.1999, (23):469-478.
[86]Ross R M, Scott E J. Three-dimensional reconstruction and modeling of complexly folded surfaces using Mathematica[J]. Computer & Geosciences. 2001,27(4):401-418.
[87]Lees J M. Xmap8:Three-dimensional GIS for geology and geophysics[J]. Seismological Research Letters.1995,66(4):33-37.
[88]Lees J M., Geotouch. Software for three and four dimensional GIS in earth sciences[J]. Computer & Geosciences.2000,26(7):751-761.
[89]徐能雄.工程岩体三维构模技术及其可视化系统研究[D].北京：中国矿业大学(北京校区).2002.
[90]徐能雄,何满朝.层状岩体三维构模方法与空间数据模型[J].中国矿业大学学报.2004.1,33(1)：103-108.
[91]何满潮,李学元,刘斌等.非层状岩体三维可视化构模技术研究[J].岩石力学与工程学报.2005.3,24(5)：774-779.
[92]徐能雄,田红,于沭.适于岩体结构三维建模的非连续地层界面整体重构[J].岩土工程学报.2007.9,29(9)：1361-1366.
[93]徐能雄,何满潮,景海河.岩体结构三维构模技术及其可视化系统研制[J].岩土工程学.2004.5,26(3)：373-377.
[94]徐能雄,何满潮.褶皱岩体三维可视化构模技术及其工程应用[J].岩土工程学.2003.7,25(4)：418-421.
[95]王笑海.基于三维拓扑格网结构的GIS地层模型研究[D].北京：中国科学院武汉岩土力学所.1999.
[96]贺怀建,白世伟,赵新华等.三维地层模型中地层划分的探讨[J].岩土力学.2001,23(5)：637-639.
[97]陈键.三维地层信息系统的建模与分析研究[D].北京：中国科学院武汉岩土力学所.2001.
[98]Jose Manuel, Vacas Pena. A program in Pascal to simulate the superposition of two or three fold systems[J]. Computer & Geosciences,2002,26(3):341-349.
[99]Zhou ZHAO, En-ke HOU, Zhi-hua ZHANG, Nian-dong DENG. Three dimensional Geological Modeling from Component-based Topological Data Model[J]. International Conference on Computer Modeling and Simulation. 2009.1:43-46.
[100]王李管,尚晓明,曾庆田.三维可视化建模技术在岩体质量评价中的应用[J].岩石力学与工程学报.2008.9,27(增2)：3655-3660.
[101]苏雨涛,李彦生,韩景芸.CT数据三维重建及可视化技术的研究[J].机械设计与制造.2009.1,(1)：191-193.
[102]徐乃平.基于断层图像序列的医学三维图像重建[D].硕士学位论文.天津师范大学.2002.3.
[103]金朝阳.医学图像三维重建及其应用[D].硕士学位论文.浙江大学.2002.6.
[104]许斌,张森,厉万庆.从序列切片重构三维对象的新方法[J].计算机学报.1994.1,17(1)：64-72.
[105]孔宪立主编.工程地质学[M].中国建筑工业出版社.1997.6.
[106]孙家齐.工程地质[M].
[107]章毓晋.图象工程(上册)：图像处理和分析[M].北京：清华大学出版社.1999.3.
[108]李弼程,彭天强,彭波等编著.智能图像处理技术[M].电子工业出版社.2004.7.
[109]Canny J F. A computational approach to edge detection[J]. IEEE Trans on PAMI,1986,8(6):679-698.
[110]Meer P, Georgescu B. Edge detection with embedded confidence[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(12): 1351-1365.
[111]万力,易昂,傅明.一种基于Canny算法的边缘提取改善方法[J].计算机技术与自动化.2003,22(1)：24-26.
[112]崔屹.图像处理与分析—数学形态学方法及应用[M].科学出版社.2000.
[113]唐常青,吕宏伯,黄铮,张方编蓍.数学形态学方法及其应用[M].科学出版社.1990.8.
[114]Eric N. Mortensen, William A. Barrett. Intelligent Scissors for Image Composition[J]. Computer Graphics.1995.8:191-198.
[115]汪斌,唐辉明,简文星等.结构面三维网络模拟在岩体质量评价中的应用[J].岩土力学.2006.4,27(4)：594-596.
[116]边肇祺,张学工.模式识别[M].清华大学出版社.2000.
[117]肖健华编著.智能模式识别方法[M].华南理工大学出版社.2005.9.
[118]谢承泮.神经网络发展综述[J].科技情报开发与经济.2006,16(12)：148-150.
[119]周志华,曹存根主编.神经网络及其应用[M].清华大学出版社.
[120]李学桥,马莉.神经网络.工程应用[M].重庆大学出版社.1996.
[121]胡守仁,余少波,戴葵.神经网络导论[M].国防科技大学出版社.1993.10.
[122]S. Grgic, M. Grgic, and M. Mrak. Reliability of Objective Picture Quality Measures Measurement[J]. Journal of Electrical Engineering.2004,55(1-2): 3-10.
[123]R. Hecht-Nielsen. Theory of Back-propagation Neural Networks[C]. Proceedings of the International Joint Conference on Neural Networks.1989,1: 593-605.
[124]张宏林.Visual C++数字图像模式识别技术及工程实践[M].人民邮电出版社.2003.2
[125]四维科技,胡小锋,赵辉编著.Visual C++/MATLAB图像处理与识别实用案例精选[M].人民邮电出版社.2004.9.
[126]高大启.有教师的线性基本函数前向三层神经网络结构研究[J].计算机学报.1998,21(1)：80-86.
[127]《数学手册》编写组.数学手册[M].高等教育出版社.2004.3.
[128]陈春萍.基于OpenGL的隧道掌子面三维重建系统的设计与实现[D].西南交通大学.2005.4.
[129]苏安,冉蜀阳,吴章文等.基于相邻层轮廓线几何形状匹配的三维重建[J].计算机应用.2009.2,29(2)：451-452.
[130]TAKASAKI H. Moire topography[J]. Appl. Opt,1970,9(9):1467-1472.
[131]G CONG, B PARVIN. An Algebraic Solution to Surface Recovery from Cross-Sectional Contours[J]. Graphical Models and Image Processing.1999, 61(4):222-243.
[132]S H LEE, D GAHN, D Y YANG. Surface reconstruction for mid-slice generation on variable lamination manufacturing[J]. Journal of Materials Processing Technology.2002,130-131:384-389.
[133]邵世禄.截头圆柱面展开图曲线方程的研究[J].甘肃农业大学学报.2002.6,37(2)：260-264.
[134]David J.Kruglinski等著.希望图书创作室译.Programming Visual C++技术内幕6.0(第五版)[M].北京希望电子出版社.1999.
[135]周长发.精通Visual C++图像编程(第三版)[M].电子工业出版社.2000.
[136]孙鑫,余安萍编著.VC++深入详解[M].北京：电子工业出版社.2007.3.
[137]明日科技,宋坤,刘锐宁等编著.Visual C++开发技术大全[M].人民邮电出版社.2007.3.
[138]孙家广等编著.计算机图形学(第三版)[M].清华大学出版社.
[139]飞思科技产品研发中心.SQL Server 2000基础与提高[M].电子工业出版社.2001.7.
[140]武洪萍、马桂婷.数据库原理及应用(SQL Server版)[M].北京大学出版社.2008.2.
[141]启明工作室编著.Visual C++ + SQL Server数据库应用实例完全解析[M].人民邮电出版社.2006.4.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |