A unified methodology for the efficient computation of discrete orthogonal image moments

被引:40
|
作者
Papakostas, G. A. [1 ]
Koulouriotis, D. E. [2 ]
Karakasis, E. G. [2 ]
机构
[1] Democritus Univ Thrace, Dept Elect & Comp Engn, GR-67100 Xanthi, Greece
[2] Democritus Univ Thrace, Dept Prod Engn & Management, GR-67100 Xanthi, Greece
关键词
Discrete image moments; Image block representation; Image slice representation; Feature extraction; Image coding; Moment calculation; ACCURATE COMPUTATION; ZERNIKE MOMENTS; RECOGNITION;
D O I
10.1016/j.ins.2009.06.033
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel methodology is proposed in this paper to accelerate the computation of discrete orthogonal image moments. The computation scheme is mainly based on a new image representation method, the image slice representation (ISR) method, according to which an image can be expressed as the outcome of an appropriate combination of several non-overlapped intensity slices. This image representation decomposes an image into a number of binary slices of the same size whose pixels come in two intensities, black or any other gray-level value. Therefore the image block representation can be effectively applied to describe the image in a more compact way. Once the image is partitioned into intensity blocks, the computation of the image moments can be accelerated, as the moments can be computed by using decoupled computation forms. The proposed algorithm constitutes a unified methodology that can be applied to any discrete moment family in the same way and produces similar promising results, as has been concluded through a detailed experimental investigation. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:3619 / 3633
页数:15
相关论文
共 50 条
  • [41] Fast computation of separable two-dimensional discrete invariant moments for image classification
    Hmimid, Abdeslam
    Sayyouri, Mhamed
    Qjidaa, Hassan
    PATTERN RECOGNITION, 2015, 48 (02) : 509 - 521
  • [42] General form for obtaining discrete orthogonal moments
    Zhu, H.
    Liu, M.
    Shu, H.
    Zhang, H.
    Luo, L.
    IET IMAGE PROCESSING, 2010, 4 (05) : 335 - 352
  • [43] New discrete orthogonal moments for signal analysis
    Asli, Barmak Honarvar Shakibaei
    Flusser, Jan
    SIGNAL PROCESSING, 2017, 141 : 57 - 73
  • [44] A NOTE ON EFFICIENT PARALLEL ALGORITHMS FOR THE COMPUTATION OF 2-DIMENSIONAL IMAGE MOMENTS
    PAN, Y
    PATTERN RECOGNITION, 1991, 24 (09) : 917 - 917
  • [45] Error Analysis in the Computation of Orthogonal Rotation Invariant Moments
    Chandan Singh
    Rahul Upneja
    Journal of Mathematical Imaging and Vision, 2014, 49 : 251 - 271
  • [46] Error Analysis in the Computation of Orthogonal Rotation Invariant Moments
    Singh, Chandan
    Upneja, Rahul
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2014, 49 (01) : 251 - 271
  • [47] Accurate Computation of Orthogonal Fourier-Mellin Moments
    Chandan Singh
    Rahul Upneja
    Journal of Mathematical Imaging and Vision, 2012, 44 : 411 - 431
  • [48] Accurate Computation of Orthogonal Fourier-Mellin Moments
    Singh, Chandan
    Upneja, Rahul
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2012, 44 (03) : 411 - 431
  • [49] Fast and accurate computation of orthogonal moments for texture analysis
    Di Ruberto, Cecilia
    Putzu, Lorenzo
    Rodriguez, Giuseppe
    PATTERN RECOGNITION, 2018, 83 : 498 - 510
  • [50] Discrete Circular Mapping for Computation of Zernike Moments
    Biswas, Rajarshi
    Biswas, Sambhunath
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, 2011, 6744 : 86 - 91