摘要
针对基于文本的图像检索(TBIR)在图像检索中的局限性,基于内容的图像检索(CBIR)出现了并迅速成为一个研究热点。文章对CBIR未来发展的8个研究方向进行了重点分析。
出处
《信息通信》
2015年第1期85-85,共1页
Information & Communications
参考文献3
-
1龙士军,侯进.在曲波域中应用统计模型的图像纹理特征提取[J].沈阳理工大学学报,2012,31(2):19-23. 被引量:1
-
2苏赋.Curvelet感兴趣区域相关图的纹理图像检索[J].上海交通大学学报,2014,48(5):653-657. 被引量:3
-
3刘丽,苏赋,田芳,卢阿娟.基于Matlab的图像感兴趣区域提取[J].现代电子技术,2013,36(8):117-120. 被引量:11
二级参考文献31
-
1刘刚.MATLAB数字图像处理[M].北京:机械工业出版社,2010.
-
2HIDEYUKI Tamura, MORI, TAKASHI Yamawaki. Textural Features Corresponding to Visual Perception [ J ]. IEEE Trans, Systems, Man and Cybernetics, 1978,8(6) :460-473.
-
3STARCK JL, CANDES EJ, DONOHO DL. The Curve- let Transform for Image Denoisong [J].IEEE Trans. Image Processing ,2002,11 ( 6 ) :670 - 684.
-
4YUAN Hua, ZHANG XiaoPing. Statistical Modeling in the Wavelet Domain for Compact Feature Extraction and Similarity Measure of Images [J].IEEE Trans. Circuits and Systems for Video Technology, 2010,20 (3) :439 -445.
-
5CANSES Emmanuel, DEMANET Laurent, DONOHO David,et al. Fast Discrete Curvelet Transforms [J]. Multiscal Modeling and Simulation, 2006, 5 ( 3 ) : 861 - 899.
-
6IJ Sumana, MM Islam, ZHANG DengSheng, et al. Content based image retrieval using curvelet transform [ C]. In Proc. 2008 IEEE 10th Workshop on. Multime- dia Signal Processing, Carins, Qld ,2008 : 11 - 16.
-
7B. S Manjunath, W. Y Ma. Texture Features For Brow- sing And Retrieval Of Image Data [ J ]. IEEE Trans, Pattern Analysis and Machine Intelligence, 1996, 18 (8) :837 -842.
-
8CHEN LianPing, Lu GuoJun, ZHANG DengSheng. Effects of Different Gabor Filter Parameters on Image Retrieval by Texture [ C ]. In Proc. 2004. Proceedings. 10th International. Multimedia Modelling Conference, 2004:273 - 278.
-
9WANG T, RUI Y, SUN J G. Constraint based region matching h:r image retrieval [J]. International Journal of Computer Vi- sion, 2004, 56( 1): 37-45.
-
10LIN Hui-bao, SI J, ABOUSLEMAN G P. Region-of-interest de- tection and its application to image segmentation and compres- sion [C]// Proceedings of International Conference on Integra- tion of Knowledge Intensive Multi- Agent System. Wahham, MA: KIMAS, 2007: 306-311.
共引文献12
-
1安慧中,刘卫东.一种基于改进的边缘插值的运动自适应去隔行算法[J].电子设计工程,2014,22(5):187-189.
-
2于飞,于木里,田永康.基于Simscape的碳化硅功率器件精确建模与仿真[J].电子测量技术,2018,41(22):21-26. 被引量:2
-
3陈宝远,李紫贺,刘景阳,兰雅琼,于晓洋.BOPET薄膜中气泡的检测及识别方法研究[J].哈尔滨理工大学学报,2015,20(1):61-65. 被引量:6
-
4刘霞,王宜志.基于改进的模板匹配的手机隔板砂粒检测[J].科学与财富,2015,7(16):121-121.
-
5郝超超,王子文.基于视觉的管道内焊缝定位[J].机械工程师,2015(9):46-49.
-
6蔡文冬,王德麾,周莹莹,樊庆文.基于数学形态学的工业损伤检测方法[J].机械,2016,43(6):67-70. 被引量:1
-
7何小凡,汪威,钟毓宁.一种基于曲面拟合的复杂表面缺陷检测方法[J].湖北工业大学学报,2017,32(1):85-88. 被引量:2
-
8单强,孙晓明.多特征分层融合医疗设备图像检索方法[J].哈尔滨理工大学学报,2017,22(2):135-139. 被引量:2
-
9程玉胜,汪辉,李雨,王振东.基于熵值优化的图像感兴趣区域提取改进方法[J].安庆师范大学学报(自然科学版),2017,23(3):48-52. 被引量:4
-
10石振刚,张靖.曲波变换尺度和方向准则图像去噪算法[J].沈阳理工大学学报,2017,36(5):39-43. 被引量:1
同被引文献27
-
1Yilldizer E, Balci A M, Hassan M, et al. Efficient content-based image retrieval using multiple support vector machines ensemble[J]. Expert Systems with Ap- plictaions, 2012, 39(3): 2385- 2396.
-
2Kovashka A, Parikh D, Grauman K. Whittlesearch : in- teractive image search with relative attribute feedback [J]. International Journal on Computer Vision, 2015, 115(2) :185 -210.
-
3Zhang H, Zha Z J, Yang Y, et al. Attribute-augmen- ted semantic hierarchy: towards bridging semantic gap and intention gap in image retrieval [ C ] //ACM Inter- national Conference on Multimedia. Barcelona, Spair: ACM ,2013 :33 -42.
-
4Oquab M, Bottou L, Laptev I, et al. Learning and transferring mid-level image representations using conv- olutional neural networks [ C ] //J IEEE Conference on Computer Vision and Pattern Recognition. Columbus, OH, United States : IEEE, 2014 : 1717 - 1724.
-
5Mansoori N S, Nejati M, Razzaghi P, et al. Bag of visual words approach for image retrieval using color information [ C ]//Conference on Electrical Engineer- ing. Mashhad : IEEE, 2013,1 - 6.
-
6Yoo D, Park C, Choi Y, et al. Intra-class key feature weighting method for vocabulary tree based image re- trieval [ C ]//Proceedings of IEEE Conference on Ubiq- uitous Robots and Ambient Intelligence. Daejeon: IEEE, 2012:517 - 520.
-
7Xu H, Wang J D, Zeng G,et al. Complementary has- hing for approximate nearest neighbor search [ C ]// Proceedings of IEEE International Conference on Com- puter Vision. Barcelona:IEEE, 2011 : 1631 - 1638.
-
8Zobel J, Moffat A. Inverted files for text search engines [J]. ACM Computing Surveys, 2006, 38(2) : 6 -10.
-
9Wang X Y, Yang M, Zhu S H, et al. Contextual weighting for vocabulary tree based image retrieval[ C] //IEEE International Conference on Computer Vision. Barcelona: IEEE,2011 : 209 - 216.
-
10Ji J Q, Yan S C, Li J M, et al. Batch-orthogonal lo- cality-sensitive hashing for angular similarity [ J ]. IEEE Transactions on Pattern Analysis and Machine In- telligence,2014,36(10) : 1963 - 1974.
引证文献2
-
1左欣,沈继锋,于化龙,高尚,徐丹,胡春龙.基于哈希编码学习的图像检索方法[J].江苏科技大学学报(自然科学版),2015,29(6):567-573. 被引量:1
-
2陈永胜,许建龙,汪亚明.结合Delaunay三角网的自适应多尺度图像重叠域配准方法[J].软件导刊,2020,19(11):206-211.
-
1焦岩,王学军,张婧.科技资源图像检索技术研究与实现[J].广西师范大学学报(自然科学版),2007,25(4):273-276.
-
2姚琪,蒋达央.电子商务中基于内容的商品图像检索技术研究[J].信息网络安全,2013(7):74-76. 被引量:5
-
3刘智.TBIR与CBIR结合检索Web图像的探讨[J].广西工学院学报,2006,17(2):55-58. 被引量:5
-
4龙泉,陆伟.基于XML的多媒体信息检索[J].情报杂志,2007,26(10):48-50. 被引量:5
-
5阿斯艳.哈米提,阿不都热西提.哈米提.基于文本的图像检索与基于内容的图像检索技术的比较研究[J].首都师范大学学报(自然科学版),2012,33(4):6-9. 被引量:16
-
6张蓓.图像检索技术的发展及现状分析[J].福建电脑,2009,25(4):42-42. 被引量:4
-
7刘艳华,周宁.图像信息资源检索技术的进展研究[J].现代情报,2006,26(1):82-85. 被引量:5
-
8韩立华,王晓芬,王玉梅.剪纸艺术多媒体交互平台中的图像检索技术研究[J].石家庄铁道大学学报(社会科学版),2013,7(4):71-75. 被引量:2