多媒体系统中基于内容的图像检索方法的研究
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摘要
随着计算机自身以及计算机应用技术的发展，图像处理技术、视频技术、数字压缩技术等都得到了迅猛的发展。文字、图像和语言等多种信息形式构成了多媒体系统。目前，多媒体系统已经越来越多地被应用到人们生活和工作的多个领域。但多媒体技术中的一个关键问题是如何对大量的图像信息进行高效、准确的检索，解决了这一“瓶颈”问题，对多媒体技术的进一步发展将有巨大的推动作用。
基于内容的图像检索(CBIR)是现有的图像检索方法中的一种，同时也是目前研究最多的一种方法。本文在分析了现有的基于内容的图像检索方法后，利用人工智能原理，将图像中的色彩信息、空间信息集成起来，提出了一种基于内容的、智能化的集成色彩空间的图像检索方法。这种方法能有效地完成对图像的检索，克服以往图像检索技术的弱点，实现智能化的检索，为多媒体信息系统的开发提供了有力的支持。
本文先详细介绍了图像处理的一些基本方法和利用小波变换的方法来提取图像的特征，然后提出了一种新的基于内容的图像检索方法，最后将提出的这种智能化的集成色彩空间的图像检索方法应用到实际的工程项目中，取得了令人满意的图像检索效果。
With the development of computer and its applications, image processing methods, video frequency technology and digital compress
technology are rapidly developed. Kinds of information such as characters, images and sounds make up of multimedia system. Nowadays, multimedia systems are more and more applied into our lives and works, but there is a key issue, that is how to retrieve images efficiently and exactly, this "bottle-neck" 's solved will support further development of multimedia technology greatly.
Content based image retrieve is one of current image retrieve methods, and a method researched most. Analyzed current image retrieve methods .using theories of Artificial Intelligence and integrating color and spatial information of image ,a new method is developed which is based on image content in this paper. This new intelligentized method could retrieve images efficiently and overcome current methods' shortcomings, and give developments of multimedia information systems very strong support.
In this paper, some basic methods of image processing and how to use wavelet transform to pick up characteristics of images are introduced in detail and an new image retrieve method are given then, at the last, apply this new method to practical project, the retrieve results are satisfying.
基于内容的图像检索(CBIR)是现有的图像检索方法中的一种，同时也是目前研究最多的一种方法。本文在分析了现有的基于内容的图像检索方法后，利用人工智能原理，将图像中的色彩信息、空间信息集成起来，提出了一种基于内容的、智能化的集成色彩空间的图像检索方法。这种方法能有效地完成对图像的检索，克服以往图像检索技术的弱点，实现智能化的检索，为多媒体信息系统的开发提供了有力的支持。
本文先详细介绍了图像处理的一些基本方法和利用小波变换的方法来提取图像的特征，然后提出了一种新的基于内容的图像检索方法，最后将提出的这种智能化的集成色彩空间的图像检索方法应用到实际的工程项目中，取得了令人满意的图像检索效果。
With the development of computer and its applications, image processing methods, video frequency technology and digital compress
technology are rapidly developed. Kinds of information such as characters, images and sounds make up of multimedia system. Nowadays, multimedia systems are more and more applied into our lives and works, but there is a key issue, that is how to retrieve images efficiently and exactly, this "bottle-neck" 's solved will support further development of multimedia technology greatly.
Content based image retrieve is one of current image retrieve methods, and a method researched most. Analyzed current image retrieve methods .using theories of Artificial Intelligence and integrating color and spatial information of image ,a new method is developed which is based on image content in this paper. This new intelligentized method could retrieve images efficiently and overcome current methods' shortcomings, and give developments of multimedia information systems very strong support.
In this paper, some basic methods of image processing and how to use wavelet transform to pick up characteristics of images are introduced in detail and an new image retrieve method are given then, at the last, apply this new method to practical project, the retrieve results are satisfying.
引文
[1] 章毓晋．图像理解与计算机视觉．清华大学出版社，1999：163-186
[2] 赵荣椿等．数字图像处理导论．西北工业大学出版社．1997：217-219
[3] 章毓晋．图像处理和分析．清华大学出版社，1999：72-99
[4] 孙兴华，郭丽，郭跃飞，杨静宇．基于目标区域的彩色图像检索研究．计算机研究与发展．2001，38(9)：1112-1120页
[5] 曹奎，冯玉才，王元珍．一种基于颜色的图像表示及全局相似检索技术．计算机研究与发展．2001，38(9)：1121-1126页
[6] 刘相滨，邹北冀．一种基于主颜色表的图像检索方法．湖南大学学报．2001，2．28(1)：35-37页
[7] 张海藩．软件工程导论．清华大学出版社，1997：25-69
[8] 蔡自兴，徐光佑．人工智能及其应用．清华大学出版社．1996，120—339
[9] George F. Luger, William A. Stubblefield. Artificial Intelligence and the Design of Expert System. University of New Mexico. 1996,90-130
[10] 杨静，Information Sharing Technology in the Multimedia Environment, IWMST 2000 International Workshop on Modern Science and Technology toward 21st Century and beyond, September 20-21,2000 Harbin China
[11] 张健沛，杨静，Transformational Basic Method from Database to Knowledge Bases, IWMST 2000 International Workshop on Modern Science and Technology toward 21st Century and beyond, September 20-21,2000 Harbin China
[12] Pavlidis T. Algorithms for Graphics and Image Processing. Computer Science Press. 1982,75-166
[13] Serra J. Image Analysis and Mathematical Morphology. Academic Press, 1982:95-117
[14] 荆仁杰，叶秀清，徐胜荣，陈存椿．计算机图形处理．清华大学出版社，1992：375-414
[15] K.R. Castlemen. Digital image processing. Prentice-Hall International Inc. 1996,95-251
[16] Shapiro L, Rosenfeld A(eds). Computer Vision and Image Processing. Academic Press, 1992:152-269
[17] Yong I T, Gerbrands J J, Vliet L J. Fundamental of Image Processing. Delft University of Technology. the Netherlands, 1995:135-301
[18] 崔屹．图像处理与分析-数学形态学方法及应用．清华大学出版社．2000：75-204
[19] Zhang Y J. Framework and experiments for image segmentation characterization. Chinese Journal of Electronics. 1998,7(4): 7-391
[20] 崔锦泰．小波分析导论．西安交通大学出版社，1995：86-91
[21] Daubechies, I.,The wavelet transform, time-frequency localization and signal analysis, IEEE Trans. On Information Theory, 1990(36):961-1005
[22] 刘贵忠，邸双亮．小波分析及应用．西安电子科技大学出版社，1992：1-200
[23] Mallat, S. Multiresolution approximations and wavelet orthonormal bases of L~2(R),Trans. Amer. Math. Soc. 315(1989),69-87
[24] 冉启文．小波分析方法及其应用．哈尔滨工业大学出版社，1995：12-19，76-80，88-92
[25] Daubechies, I..Wavelets. CBMS-NSF Series in Appl. Math..SIAM Publ. Philadelphia. 1992:1-30
[26] 刘忠伟，章毓晋．综合利用颜色和纹理特征的图像检索．通信学报．1998，20(5)：36-40
[27] Zhang Y J, Liu Z W, He Y. Comparison and improvement of color-based image retrieval techniques.1998. SPIE3312:371-382
[28] 王惠锋，金翔宇，孙正兴．基于语义的图像检索方法研究综述．计算机工程．2001，27(8)：3-5页
[29] Abreu E., Lightstone M., Mitra S.K. and Arakawa K., A new efficient approach for the removal of impulse noise from highly corrupued images. IEEE Tran. on Image Proc. 1996,5(6):1012-1025
[30] Serra J. Image Analysis and Mathematical Morphology. Academic Press, 1982:95-117
[31] A.K. Jain. Fundamentals of Digital Image Processing. Prentice Hall Inc, 1989:78-151
[32] 刘传憬，黄煜，陈晓明．多格式图像程序设计入门．人民邮电出版社，1995：220-357
[2] 赵荣椿等．数字图像处理导论．西北工业大学出版社．1997：217-219
[3] 章毓晋．图像处理和分析．清华大学出版社，1999：72-99
[4] 孙兴华，郭丽，郭跃飞，杨静宇．基于目标区域的彩色图像检索研究．计算机研究与发展．2001，38(9)：1112-1120页
[5] 曹奎，冯玉才，王元珍．一种基于颜色的图像表示及全局相似检索技术．计算机研究与发展．2001，38(9)：1121-1126页
[6] 刘相滨，邹北冀．一种基于主颜色表的图像检索方法．湖南大学学报．2001，2．28(1)：35-37页
[7] 张海藩．软件工程导论．清华大学出版社，1997：25-69
[8] 蔡自兴，徐光佑．人工智能及其应用．清华大学出版社．1996，120—339
[9] George F. Luger, William A. Stubblefield. Artificial Intelligence and the Design of Expert System. University of New Mexico. 1996,90-130
[10] 杨静，Information Sharing Technology in the Multimedia Environment, IWMST 2000 International Workshop on Modern Science and Technology toward 21st Century and beyond, September 20-21,2000 Harbin China
[11] 张健沛，杨静，Transformational Basic Method from Database to Knowledge Bases, IWMST 2000 International Workshop on Modern Science and Technology toward 21st Century and beyond, September 20-21,2000 Harbin China
[12] Pavlidis T. Algorithms for Graphics and Image Processing. Computer Science Press. 1982,75-166
[13] Serra J. Image Analysis and Mathematical Morphology. Academic Press, 1982:95-117
[14] 荆仁杰，叶秀清，徐胜荣，陈存椿．计算机图形处理．清华大学出版社，1992：375-414
[15] K.R. Castlemen. Digital image processing. Prentice-Hall International Inc. 1996,95-251
[16] Shapiro L, Rosenfeld A(eds). Computer Vision and Image Processing. Academic Press, 1992:152-269
[17] Yong I T, Gerbrands J J, Vliet L J. Fundamental of Image Processing. Delft University of Technology. the Netherlands, 1995:135-301
[18] 崔屹．图像处理与分析-数学形态学方法及应用．清华大学出版社．2000：75-204
[19] Zhang Y J. Framework and experiments for image segmentation characterization. Chinese Journal of Electronics. 1998,7(4): 7-391
[20] 崔锦泰．小波分析导论．西安交通大学出版社，1995：86-91
[21] Daubechies, I.,The wavelet transform, time-frequency localization and signal analysis, IEEE Trans. On Information Theory, 1990(36):961-1005
[22] 刘贵忠，邸双亮．小波分析及应用．西安电子科技大学出版社，1992：1-200
[23] Mallat, S. Multiresolution approximations and wavelet orthonormal bases of L~2(R),Trans. Amer. Math. Soc. 315(1989),69-87
[24] 冉启文．小波分析方法及其应用．哈尔滨工业大学出版社，1995：12-19，76-80，88-92
[25] Daubechies, I..Wavelets. CBMS-NSF Series in Appl. Math..SIAM Publ. Philadelphia. 1992:1-30
[26] 刘忠伟，章毓晋．综合利用颜色和纹理特征的图像检索．通信学报．1998，20(5)：36-40
[27] Zhang Y J, Liu Z W, He Y. Comparison and improvement of color-based image retrieval techniques.1998. SPIE3312:371-382
[28] 王惠锋，金翔宇，孙正兴．基于语义的图像检索方法研究综述．计算机工程．2001，27(8)：3-5页
[29] Abreu E., Lightstone M., Mitra S.K. and Arakawa K., A new efficient approach for the removal of impulse noise from highly corrupued images. IEEE Tran. on Image Proc. 1996,5(6):1012-1025
[30] Serra J. Image Analysis and Mathematical Morphology. Academic Press, 1982:95-117
[31] A.K. Jain. Fundamentals of Digital Image Processing. Prentice Hall Inc, 1989:78-151
[32] 刘传憬，黄煜，陈晓明．多格式图像程序设计入门．人民邮电出版社，1995：220-357