基于数字图像处理对沉淀池矾花控制系统的算法研究
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摘要
近年来，随着计算机硬件和软件技术的飞速发展，数字图像处理技术进入了不同层次的工业领域，走向更加深入的应用。但在工程实践应用中，仍存在着一定的限制，对具体问题没有固定统一的算法来解决。目前，对具体问题的具体研究仍然是一个具有挑战性的课题。
本文基于数字图像处理，研究、开发了一套自来水厂沉淀池矾花控制系统自动化的方案，文中给出了该系统的设计思想、设计框图、详细设计和图像处理的具体算法。
本系统分软件和硬件两大部分，本文着重研究了系统的软件部分：图像采集和图像处理，其中又重点研究了图像处理部分。本文针对采集的矾花图像的特点，进行特征抽取，主要提取了图像的密度特征和纹理特征，构造多分类器组合进行图像识别。由于现有的算法都不能很好的满足实际系统的需要，因此，本文基于图像工程的思想，对基本算法加以改进，提出并实现了新的算法来识别矾花图像。实验结果表明，本文研究设计的系统是合理的，提出的算法是切实可行的，能满足工业实际的要求。
With the quick development of software and hardware technology of computer, digital image processing has applied to all levels in industry territory, more and more embedded applications of it have taken place. However, there is some limitation in practice. There is still no one algorithm which can adapt to solve all problems. In fact, it is still a task of great challenge to solve special problems with special methods in practice.
Based on digital image processing, a scheme of Alum Control System in precipitator of waterworks ,which include designing thinking, frame , measure and researching algorithms, is researched and exploited in the paper.
The Alum Control System is made up of hardware and software, and the software consists of image collecting and processing. In the paper, image processing is the emphasis. According to the features of alum image, some features are abstracted which includes the density and texture. Because present arithmetic can't be used to get the perfect results, based on the thinking of Image Engineering, new arithmetic is brought forward and used in the paper. The results of experiments show that the arithmetic is effective, and the system is high effective and reliable.
本文基于数字图像处理，研究、开发了一套自来水厂沉淀池矾花控制系统自动化的方案，文中给出了该系统的设计思想、设计框图、详细设计和图像处理的具体算法。
本系统分软件和硬件两大部分，本文着重研究了系统的软件部分：图像采集和图像处理，其中又重点研究了图像处理部分。本文针对采集的矾花图像的特点，进行特征抽取，主要提取了图像的密度特征和纹理特征，构造多分类器组合进行图像识别。由于现有的算法都不能很好的满足实际系统的需要，因此，本文基于图像工程的思想，对基本算法加以改进，提出并实现了新的算法来识别矾花图像。实验结果表明，本文研究设计的系统是合理的，提出的算法是切实可行的，能满足工业实际的要求。
With the quick development of software and hardware technology of computer, digital image processing has applied to all levels in industry territory, more and more embedded applications of it have taken place. However, there is some limitation in practice. There is still no one algorithm which can adapt to solve all problems. In fact, it is still a task of great challenge to solve special problems with special methods in practice.
Based on digital image processing, a scheme of Alum Control System in precipitator of waterworks ,which include designing thinking, frame , measure and researching algorithms, is researched and exploited in the paper.
The Alum Control System is made up of hardware and software, and the software consists of image collecting and processing. In the paper, image processing is the emphasis. According to the features of alum image, some features are abstracted which includes the density and texture. Because present arithmetic can't be used to get the perfect results, based on the thinking of Image Engineering, new arithmetic is brought forward and used in the paper. The results of experiments show that the arithmetic is effective, and the system is high effective and reliable.
引文
[1] 夏良正．数字图像处理．南京：东南大学出版社，1999，9．
[2] K. R. Castleman. Digital Image Processing. Pretice Hall, 1998,1.
[3] 阮秋琦．数字图像处理学．北京：电子工业出版社．2001，1．
[4] 何斌等．Visual C++数字图像处理．北京：人民邮电出版社．2001，4．
[5] 杨枝灵，王开等．Visual C++数字图像获取、处理及实践应用．北京：人民邮电出版社．2003，1．
[6] IEEE Std 610.4-1990, IEEE Standard Glossary of Image Processing and Pattern Recognition Terminology, IEEE, New York, 1990.
[7] Zhang Yujin. Image engineering in China, 1995[J] . Journal of Image and Graphics, 1996,1(1):78-83.
[8] 章毓晋．中国图像工程及当前的几个研究热点．计算机辅助设计与图形学学报．2002，6．
[9] David J．Kruglinski著，潘爱民，王国印译．Visual C++技术内幕(第四版)．北京：清华大学出版社．2001，11．
[10] Stanley B．Lippman，Josee Lajoie著，潘爱民，张丽译．C++Primer(第三版)．北京：中国电力出版社．2002，5．
[11] 刘丁，毛德柱，王云飞．USB在数据采集系统中的应用．自动化与仪器仪表．2000，(4)：37-39．
[12] 张金波，张学武．制约数据远距离传输的因素及解决方法．微型机与应用．2000，(10)：25-26．
[13] 许刚，廖斌，李承毅．JPEG图像文件格式分析．计算机系统应用．1998,(10)：37-39．
[14] Hieischer, A.H., Kiose,A.D.,Hanson , K.M.Gradient-Based iterative image reconstruction scheme for time-resolved optical tomography. IEEE Transactions on Medical
Imaging,1999,18(3):262-271.
[15] Pan, Xiao-chuan. Consistency condition and linear reconstruction methods in diffraction tomography. IEEE Transactions on Medical Imaging, 2000,19(1):51-54.
[16] Spall , J.C., Cristion, J.A.Model-Free control of nonlinear stochastic systems with discrete-time measurements. IEEE Transactions on Automatic Control, 1998,43(9):1198-1210.
[17] 钱徽，朱淼良．大气退化的自然山体图像复原研究．计算机辅助设计与图形学学报．2002，(6)：526-529．
[18] 刘传才，傅消祥．基于随机扰动梯度近似的图像复原与重构算法．软件学报．2002，13(10)：2044-2050．
[19] 顾尔丹，许端清，陈纯．结合Gamma修正的色彩量化新算法．计算机辅助设计与图形学学报．2002，4：350-360．
[20] 任明武，曹雨龙，杨静宇，唐振民．复杂条件下的船舶目标检测的图象预处理．计算机工程．2000，(10)：68-70．
[21] D-M.Tsai and Y-h.Cheng, A fast histogram-clustering approach for multi-levelthresholding, Pattern Recognition Lett. 1992-13: 245-252.
[22] Kamel M, Zhao A. Extraction of Binary Character/Graphics Images from Grayscale Document Images. Graphical Models and linage Processing, 1993,55(3):203-217.
[23] J-C.Olivo, Automatic threshold selection using the wavelet transform, CVGIP, 1994-56:205-218.
[24] Parker J R.Gray Level Thresholding in Badly Illustrated Images IEEE Trans on Pattern Analysis and Machine Intelligence. 1991, 13(8):813-819.
[25] Dizenzo S, Cinque L, Levialdi S.Image Thresholding Using Fuzzy Entropies. IEEE Trans on System, Man, and Cybernetics,B. 1998,28(1):15-23.
[26] A.D.brink , Thresholding of digital images using two-dimensional entropics. Pattern Recognization, 1992,25:803-808.
[27] Bertalmio,M.,Sapiro,G.,Randall,G.Region tracking on level-set methods. IEEE Transactions on Medical Imaging,1999,18(5):448-451.
[28] 林瑶，田捷．医学图像分割方法综述．模式识别与人工智能．2002，(6)：192-204．
[29] 朱付平，田捷等．基于Level Set方法的医学图像分割．软件学报．2002，13(9)：1866．1872．
[30] 赵雪松，陈淑珍．邮政信封图像的分割．计算机辅助设计与图形学学报．2002，(7)：701-704．
[31] 梁华为．直接从双峰直方图确定二值化阈值．模式识别与人工智能．2002，(6)：253-255．
[32] 陈果，左洪福．图像分割的二维最大熵遗传算法．计算机辅助设计与图形学学报．2002，(6)：530-534．
[33] 王敏，骆惠，黄心汉．一种新的自动多阈值图像分割方法．信号处理．2000，(3)：90-94．
[34] 王俊杰，黄心汉．一种对图像进行快速二值化处理的方法．电子技术应用．1998，(10)：16-17．
[35] 赵立初，施鹏飞．基于动态阈值选择和细化算法的角膜细胞轮廓抽取．上海交通大学学报．1998，(9)：67-69．
[36] 李晓春等．复杂场景中动目标图像分割的一种快速算法．清华大学学报(自然科学版)．1997，(8)：19-21．
[37] 何振亚，鲍锴等．纹理图象分割的分形方法研究擞据采集与处理．1996，(9)：163-167．
[38] A zencott R, Wang J P, Younes L. Texture classification using windowed fourier filters. IEEE Trans on PAMI., 1997,19(2): 148-152.
[39] Pichler Olaf. A comparision of texture feature extraction using adaptive Gabor filtering, pyram idal and tree-structured wavelet transforms[J].Pattern Recognition, 1996,29(5):733-742.
[40] Chang T, Kuo CC J. Texture analysis and classification with tree-structured wavelet transform[J].IEEE Trans Image Processing, 1993,2(10):429-431.
[41] Bovik A C, Clark M.Multichannel texture analysis using localized spatial filters[J].IEEE Trans P A M 1,1990,12(1):55-73.
[42] 张宏林等．Visual C++数字图像模式识别技术及工程实践．北京：人民邮电出版社，2003，2．
[43] 郭捷，施鹏飞．基于颜色和纹理分析的车牌定位方法．中国图象图形学报．2002．5：472-476．
[44] 杨淑莹，胡军，曹作良．基于图像纹理分析的目标物体识别方法．天津理工学院学报．2001，4：31-33．
[45] 郑敏等．利用互相关函数进行环境激励下的模态分析．航空学报．2000，11：535-537．
[46] 吴均，赵忠明．利用基于小波的尺度共生矩阵进行纹理分析．遥感学报．2001，2：100-103．
[47] Xu L, Krzyzak A, Suen C Y. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans SMC, 1992,22(3):418-430.
[48] Huang Y S, Liu K, Suen C Y. The combination of multiple classifiers by a neural network approach. Int Journal of Pattern Recognition and Artificial Intelligence, 1995,19(3):579-597.
[49] Cao J, Ahmadi M, Shridhar M. Recognition of handwritten numerals with multiple feature and multistage classifier. Pattern Recognition, 1995,28(2):153-160.
[50] 韩宏，杨静宁．多分类器组合及其应用．计算机科学．2000，1：58-61．
[51] 候平魁，史习智等．水下目标识别的特征融合分类器设计．电子学报．2001，4：443-446．
[52] 吕岳，施鹏飞．改进的贝叶斯多分类器组合规则．数据采集与处理．2000，6：204-207．
[53] 胡钟山，娄震等．基于多分类器组合的手写体数字识别．计算机学报．1999，4：369-374．
[2] K. R. Castleman. Digital Image Processing. Pretice Hall, 1998,1.
[3] 阮秋琦．数字图像处理学．北京：电子工业出版社．2001，1．
[4] 何斌等．Visual C++数字图像处理．北京：人民邮电出版社．2001，4．
[5] 杨枝灵，王开等．Visual C++数字图像获取、处理及实践应用．北京：人民邮电出版社．2003，1．
[6] IEEE Std 610.4-1990, IEEE Standard Glossary of Image Processing and Pattern Recognition Terminology, IEEE, New York, 1990.
[7] Zhang Yujin. Image engineering in China, 1995[J] . Journal of Image and Graphics, 1996,1(1):78-83.
[8] 章毓晋．中国图像工程及当前的几个研究热点．计算机辅助设计与图形学学报．2002，6．
[9] David J．Kruglinski著，潘爱民，王国印译．Visual C++技术内幕(第四版)．北京：清华大学出版社．2001，11．
[10] Stanley B．Lippman，Josee Lajoie著，潘爱民，张丽译．C++Primer(第三版)．北京：中国电力出版社．2002，5．
[11] 刘丁，毛德柱，王云飞．USB在数据采集系统中的应用．自动化与仪器仪表．2000，(4)：37-39．
[12] 张金波，张学武．制约数据远距离传输的因素及解决方法．微型机与应用．2000，(10)：25-26．
[13] 许刚，廖斌，李承毅．JPEG图像文件格式分析．计算机系统应用．1998,(10)：37-39．
[14] Hieischer, A.H., Kiose,A.D.,Hanson , K.M.Gradient-Based iterative image reconstruction scheme for time-resolved optical tomography. IEEE Transactions on Medical
Imaging,1999,18(3):262-271.
[15] Pan, Xiao-chuan. Consistency condition and linear reconstruction methods in diffraction tomography. IEEE Transactions on Medical Imaging, 2000,19(1):51-54.
[16] Spall , J.C., Cristion, J.A.Model-Free control of nonlinear stochastic systems with discrete-time measurements. IEEE Transactions on Automatic Control, 1998,43(9):1198-1210.
[17] 钱徽，朱淼良．大气退化的自然山体图像复原研究．计算机辅助设计与图形学学报．2002，(6)：526-529．
[18] 刘传才，傅消祥．基于随机扰动梯度近似的图像复原与重构算法．软件学报．2002，13(10)：2044-2050．
[19] 顾尔丹，许端清，陈纯．结合Gamma修正的色彩量化新算法．计算机辅助设计与图形学学报．2002，4：350-360．
[20] 任明武，曹雨龙，杨静宇，唐振民．复杂条件下的船舶目标检测的图象预处理．计算机工程．2000，(10)：68-70．
[21] D-M.Tsai and Y-h.Cheng, A fast histogram-clustering approach for multi-levelthresholding, Pattern Recognition Lett. 1992-13: 245-252.
[22] Kamel M, Zhao A. Extraction of Binary Character/Graphics Images from Grayscale Document Images. Graphical Models and linage Processing, 1993,55(3):203-217.
[23] J-C.Olivo, Automatic threshold selection using the wavelet transform, CVGIP, 1994-56:205-218.
[24] Parker J R.Gray Level Thresholding in Badly Illustrated Images IEEE Trans on Pattern Analysis and Machine Intelligence. 1991, 13(8):813-819.
[25] Dizenzo S, Cinque L, Levialdi S.Image Thresholding Using Fuzzy Entropies. IEEE Trans on System, Man, and Cybernetics,B. 1998,28(1):15-23.
[26] A.D.brink , Thresholding of digital images using two-dimensional entropics. Pattern Recognization, 1992,25:803-808.
[27] Bertalmio,M.,Sapiro,G.,Randall,G.Region tracking on level-set methods. IEEE Transactions on Medical Imaging,1999,18(5):448-451.
[28] 林瑶，田捷．医学图像分割方法综述．模式识别与人工智能．2002，(6)：192-204．
[29] 朱付平，田捷等．基于Level Set方法的医学图像分割．软件学报．2002，13(9)：1866．1872．
[30] 赵雪松，陈淑珍．邮政信封图像的分割．计算机辅助设计与图形学学报．2002，(7)：701-704．
[31] 梁华为．直接从双峰直方图确定二值化阈值．模式识别与人工智能．2002，(6)：253-255．
[32] 陈果，左洪福．图像分割的二维最大熵遗传算法．计算机辅助设计与图形学学报．2002，(6)：530-534．
[33] 王敏，骆惠，黄心汉．一种新的自动多阈值图像分割方法．信号处理．2000，(3)：90-94．
[34] 王俊杰，黄心汉．一种对图像进行快速二值化处理的方法．电子技术应用．1998，(10)：16-17．
[35] 赵立初，施鹏飞．基于动态阈值选择和细化算法的角膜细胞轮廓抽取．上海交通大学学报．1998，(9)：67-69．
[36] 李晓春等．复杂场景中动目标图像分割的一种快速算法．清华大学学报(自然科学版)．1997，(8)：19-21．
[37] 何振亚，鲍锴等．纹理图象分割的分形方法研究擞据采集与处理．1996，(9)：163-167．
[38] A zencott R, Wang J P, Younes L. Texture classification using windowed fourier filters. IEEE Trans on PAMI., 1997,19(2): 148-152.
[39] Pichler Olaf. A comparision of texture feature extraction using adaptive Gabor filtering, pyram idal and tree-structured wavelet transforms[J].Pattern Recognition, 1996,29(5):733-742.
[40] Chang T, Kuo CC J. Texture analysis and classification with tree-structured wavelet transform[J].IEEE Trans Image Processing, 1993,2(10):429-431.
[41] Bovik A C, Clark M.Multichannel texture analysis using localized spatial filters[J].IEEE Trans P A M 1,1990,12(1):55-73.
[42] 张宏林等．Visual C++数字图像模式识别技术及工程实践．北京：人民邮电出版社，2003，2．
[43] 郭捷，施鹏飞．基于颜色和纹理分析的车牌定位方法．中国图象图形学报．2002．5：472-476．
[44] 杨淑莹，胡军，曹作良．基于图像纹理分析的目标物体识别方法．天津理工学院学报．2001，4：31-33．
[45] 郑敏等．利用互相关函数进行环境激励下的模态分析．航空学报．2000，11：535-537．
[46] 吴均，赵忠明．利用基于小波的尺度共生矩阵进行纹理分析．遥感学报．2001，2：100-103．
[47] Xu L, Krzyzak A, Suen C Y. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans SMC, 1992,22(3):418-430.
[48] Huang Y S, Liu K, Suen C Y. The combination of multiple classifiers by a neural network approach. Int Journal of Pattern Recognition and Artificial Intelligence, 1995,19(3):579-597.
[49] Cao J, Ahmadi M, Shridhar M. Recognition of handwritten numerals with multiple feature and multistage classifier. Pattern Recognition, 1995,28(2):153-160.
[50] 韩宏，杨静宁．多分类器组合及其应用．计算机科学．2000，1：58-61．
[51] 候平魁，史习智等．水下目标识别的特征融合分类器设计．电子学报．2001，4：443-446．
[52] 吕岳，施鹏飞．改进的贝叶斯多分类器组合规则．数据采集与处理．2000，6：204-207．
[53] 胡钟山，娄震等．基于多分类器组合的手写体数字识别．计算机学报．1999，4：369-374．
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