Content based image retrieval in a web 3.0 environment

被引:0
作者
Aun Irtaza
M. Arfan Jaffar
Mannan Saeed Muhammad
机构
[1] National University of Computer & Emerging Sciences,
[2] College of Computer and Information Sciences,undefined
[3] Al Imam Mohammad Ibn Saud Islamic University (IMSIU),undefined
[4] Hanyang University,undefined
来源
Multimedia Tools and Applications | 2015年 / 74卷
关键词
Content-Based Image Retrieval (CBIR); Genetic algorithms; Relevance feedback; Support vector machines; Social media;
D O I
暂无
中图分类号
学科分类号
摘要
With the dramatic growth of Internet and multimedia applications, a virtually free worldwide digital distribution infrastructure has emerged. The concept of intelligent web or web 3.0 gives an opportunity to its users to share information in a way that could reach a broader audience and provide that audience with much deeper accessibility and interpretation of the information. Legacy image search systems which rely on the text annotations like keywords, and captions to retrieve images are not appropriate in web 3.0 architecture. Because these systems are unable to retrieve images which do not have this associated information. Also these systems suffers from the high cost of manual text annotations and linguistic problems as well while sharing and retrieving images. Therefore to handle these issues an image retrieval and management technique is presented in this paper which considers the actual image contents and do not rely on the associated metadata. Our content based image retrieval technique incorporates Genetic algorithms with support vector machines and user feedbacks for image retrieval purposes, and assures the effective retrieval and sharing of images by taking the users considerations into an account.
引用
收藏
页码:5055 / 5072
页数:17
相关论文
共 88 条
  • [1] Andrysiak T(2005)Texture image retrieval based on hierarchal Gabor filters Int J Appl Math Comput Sci 15 471-480
  • [2] Chora’s M(2010)Biased discriminant Euclidean embedding for content-based image retrieval IEEE Trans Image Process 19 545-554
  • [3] Bian W(2011)Learning effective color features for content based image retrieval in dermatology Elsevier J Pattern Recognit 44 1892-1902
  • [4] Tao D(2005)CLUE: cluster-based retrieval of images by unsupervised learning IEEE Trans Image Process 14 1187-1201
  • [5] Bunte K(1994)Efficient and effective querying by image content J Intell Inf Syst 3 231-262
  • [6] Biehl M(1995)Query by image and video content: the QBIC system IEEE Comput 28 23-32
  • [7] Jonkman MF(2009)Texture based image indexing and retrieval Inter Jour Comp Sci Net Security 9 206-210
  • [8] Petkov N(1997)Visual information retrieval Commun ACM 40 70-79
  • [9] Chen Y(2004)Content based image retrieval using motif co-occurrence matrix Image Vis Comput 22 1211-1220
  • [10] Wang JZ(1993)Texture classification by wavelet packets signature IEEE Trans Pattern Anal Mach Intell 15 1186-1191