彩色图像数据库中目标特征数据挖掘方法
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摘要
针对由于彩色图像数据特征较多使得目标特征挖掘容易出现不确定性的问题,提出一种新的彩色图像数据库中目标特征数据挖掘方法.采用减法聚类算法对彩色图像数据进行聚类,采用离群点检测技术对聚类数据进行分类处理,采用量子行为粒子群优化方法选取最优目标图像特征数据,并与结构相似度计算方法相结合,实现对最优目标图像特征数据的挖掘.结果证明,该方法相比传统的挖掘方法,其挖掘召回率降低了约17%,挖掘精确度提高了约28.6%.
Aiming at the problem that the uncertainty caused by the multiple features of color image data is easy to appear in the object feature mining,a newmining method for the target feature data in the color image database was proposed. The color image data were clustered with the subtractive clustering method,and the clustered data were classified with the outlier detection technique. In addition,the optimal target image feature data were selected with the quantum behaved particle swarm optimization method. In combination with the structural similarity calculation method,the mining of optimal target image feature data was realized. The results showthat compared with the traditional mining method,the recall rate of proposed method reduces by about 17%,while the mining accuracy increases by about 28. 6%.
Aiming at the problem that the uncertainty caused by the multiple features of color image data is easy to appear in the object feature mining,a newmining method for the target feature data in the color image database was proposed. The color image data were clustered with the subtractive clustering method,and the clustered data were classified with the outlier detection technique. In addition,the optimal target image feature data were selected with the quantum behaved particle swarm optimization method. In combination with the structural similarity calculation method,the mining of optimal target image feature data was realized. The results showthat compared with the traditional mining method,the recall rate of proposed method reduces by about 17%,while the mining accuracy increases by about 28. 6%.
引文
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[17]刘伟,孟小峰,凌妍妍.一种基于图模型的Web数据库采样方法[J].软件学报,2008,19(2):179-193.(LIU Wei,MENG Xiao-feng,LING Yan-yan.A graph-based approach for web database sampling[J].Journal of Software,2008,19(2):179-193.)
[2]胡文瑜,孙志挥,吴英杰.数据挖掘取样方法研究[J].计算机研究与发展,2011,48(1):45-54.(HU Wen-yu,SUN Zhi-hui,WU Ying-jie.Study of sampling methods on data mining and stream mining[J].Journal of Computer Research and Development,2011,48(1):45-54.)
[3]汤恒耀,胡志华.基于链距离估计的非显著特征数据挖掘算法[J].科技通报,2015,31(6):142-144.(TANG Heng-yao,HU Zhi-hua.Non significant features data mining algorithm based on chain distance dstimation[J].Bulletin of Science and Technology,2015,31(6):142-144.)
[4]武靖娜,杨姝,王剑辉.一种分布式大数据挖掘的快速在线学习算法[J].沈阳师范大学学报(自然科学版),2016,34(1):100-104.(WU Jing-na,YANG Shu,WANG Jian-hui.A newfast online learning algorithm based on distributed mining of big data[J].Journal of Shenyang Normal University(Natural Science Edition),2016,34(1):100-104.)
[5]李骏骁.多层差异网络深度入侵数据挖掘方法研究[J].计算机仿真,2015,32(4):235-238.(LI Jun-xiao.Multilayer network intrusion data mining depth difference method research[J].Computer Simulation,2015,32(4):235-238.)
[6]康凤,蒋小惠,冯梅.网络伪装隐形文本特征检测及数据挖掘方法[J].科技通报,2014,30(4):113-115.(KANG Feng,JIANG Xiao-hui,FENG Mei.Method of data mining and hidden text data feature detection for network intrusion[J].Bulletin of Science and Technology,2014,30(4):113-115.)
[7]米晓萍,李雪梅.基于信息融合度传递的频域徙动入侵特征挖掘算法[J].计算机科学,2015,42(3):224-227.(MI Xiao-ping,LI Xue-mei.Mining algorithm of frequency domain migration intrusion feature based on information fusion transfer[J].Computer Science,2015,42(3):224-227.)
[8]陈佳,胡波,左小清,等.利用手机定位数据的用户特征挖掘[J].武汉大学学报(信息科学版),2014,39(6):734-738.(CHEN Jia,HU Bo,ZUO Xiao-qing,et al.Personal profile mining based on mobile phone location data[J].Geomatics and Information Science of Wuhan University,2014,39(6):734-738.)
[9]陈向东,李平.基于色彩特征的CAMSHIFT视频图像汽车流量检测[J].沈阳工业大学学报,2015,37(2):183-188.(CHEN Xiang-dong,LI Ping.Vehicle flowdetection with CAMSHIFT video images based on color feature[J].Journal of Shenyang University of Technology,2015,37(2):183-188.)
[10]马瑞,周谢,彭舟,等.考虑气温因素的负荷特性统计指标关联特征数据挖掘[J].中国电机工程学报,2015,35(1):43-51.(MA Rui,ZHOU Xie,PENG Zhou,et al.Data mining on correlation feature of load characteristics statistical indexes considering temperature[J].Proceedings of the CSEE,2015,35(1):43-51.)
[11]王小平.基于运动背景的自适应视频对象分割算法[J].重庆邮电大学学报(自然科学版),2016,28(1):95-99.(WANG Xiao-ping.Adaptive video object segmentation algorithm based on background motion[J].Journal of Chongqing University of Posts and Telecommunications(Nature Science Edition),2016,28(1):95-99.)
[12]黄斌,许舒人,蒲卫.基于MapReduce的数据挖掘平台设计与实现[J].计算机工程与设计,2013,34(2):495-501.(HUANG Bin,XU Shu-ren,PU Wei.Design and implementation of MapReduce-based data mining platform[J].Computer Engineering and Design,2013,34(2):495-501.)
[13]余旺盛,田孝华,侯志强.基于区域边缘统计的图像特征描述新方法[J].计算机学报,2014,37(6):1398-1410.(YU Wang-sheng,TIAN Xiao-hua,HOU Zhi-qiang.A newimage feature descriptor based on region edge statistical[J].Chninese Journal of Computers,2014,37(6):1398-1410.)
[14]柯丹丹,蔡光程,曹倩倩.基于图像特征的各向异性扩散去噪方法[J].计算机应用,2012,32(3):742-745.(KE Dan-dan,CAI Guang-cheng,CAO Qian-qian.Anisotropic diffusion denoising method based on image feature[J].Journal of Computer Applications,2012,32(3):742-745.)
[15]朱阅岸,周烜,张延松,等.多核处理器下事务型数据库性能优化技术综述[J].计算机学报,2015,38(9):1865-1879.(ZHU Yue-an,ZHOU Xuan,ZHANG Yan-song,et al.A survey of optimization methods for transactional daabase in multi-core era[J].Chninese Journal of Computers,2015,38(9):1865-1879.)
[16]陆会明,周钊,廖常斌.基于实时数据库系统的历史数据处理[J].电力自动化设备,2009,29(3):127-131.(LU Hui-ming,ZHOU Zhao,LIAO Chang-bin.Historical data processing in real-time database system[J].Electric Power Automation Equipment,2009,29(3):127-131.)
[17]刘伟,孟小峰,凌妍妍.一种基于图模型的Web数据库采样方法[J].软件学报,2008,19(2):179-193.(LIU Wei,MENG Xiao-feng,LING Yan-yan.A graph-based approach for web database sampling[J].Journal of Software,2008,19(2):179-193.)