Object category retrieval for multimedia databases

被引:0
|
作者
Shao, Ling [1 ]
Li, Ping [1 ]
Kirenko, Ihor [1 ]
机构
[1] Philips Res Labs, POB 80000, Eindhoven, Netherlands
关键词
content-based image retrieval; salient region detection; moment invariants; object category retrieval;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a novel content-based object category retrieval technique using salient regions and moment invariants is presented. The salient regions are detected according to Shannon entropy and scale selection. They are invariant under various viewpoint transformations, and intra-class variations. These regions are the most informative ones, hence are potentially more effective for image indexing and retrieval. Generalized colour moment invariants are used as the invariant descriptor on the selected salient regions to characterize them. The distance of the moment invariant vectors calculated from regions of different images is evaluated to be the similarity measure between images. The experimental results show that our proposed method is very efficient and effective on retrieving object categories from image databases.
引用
收藏
页码:139 / +
页数:2
相关论文
共 50 条
  • [21] An index and retrieval framework integrating perceptive features and semantics for multimedia databases
    Shi, Zhiping
    He, Qing
    Shi, Zhongzhi
    MULTIMEDIA TOOLS AND APPLICATIONS, 2009, 42 (02) : 207 - 231
  • [22] Spatial-match iconic image retrieval with ranking in multimedia databases
    Chang, JW
    Kim, YJ
    ADVANCES IN WEB-AGE INFORMATION MANAGEMENT, PROCEEDINGS, 2001, 2118 : 3 - 13
  • [23] Audio classification using acoustic images for retrieval from multimedia databases
    Paraskevas, I
    Chilton, E
    PROCEEDINGS EC-VIP-MC 2003, VOLS 1 AND 2, 2003, : 187 - 192
  • [24] An index and retrieval framework integrating perceptive features and semantics for multimedia databases
    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
    Multimedia Tools Appl, 1600, 2 (207-231):
  • [25] An object-oriented uncertainty retrieval approach for graphics databases
    Itoga, SY
    Ke, XD
    Liu, Y
    DESIGN OF COMPUTING SYSTEMS: SOCIAL AND ERGONOMIC CONSIDERATIONS, 1997, 21 : 683 - 686
  • [26] Application of planar shape comparison to object retrieval in image databases
    Latecki, LJ
    Lakämper, R
    PATTERN RECOGNITION, 2002, 35 (01) : 15 - 29
  • [27] Mobile object retrieval in server-based image databases
    Manger, D.
    Pagel, F.
    Widak, H.
    MOBILE MULTIMEDIA/IMAGE PROCESSING, SECURITY, AND APPLICATIONS 2013, 2013, 8755
  • [28] Facilitating object-based navigation through multimedia Web databases
    Hirata, K
    Mukherjea, S
    Li, WS
    Okamura, Y
    Hara, Y
    THEORY AND PRACTICE OF OBJECT SYSTEMS, 1998, 4 (04): : 261 - 283
  • [29] MEMORI: MHEG engine or multimedia information object retrieval and interchange
    Chung, HS
    Chung, KS
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 1996, E79D (06) : 680 - 686
  • [30] A cost driven disk scheduling algorithm for multimedia object retrieval
    Ghandeharizadeh, S
    Huang, LG
    Kamel, I
    IEEE TRANSACTIONS ON MULTIMEDIA, 2003, 5 (02) : 186 - 196