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Classification of Coral Reef Submarine Images and Videos Using a Novel Z with Tilted Z Local Binary Pattern (Z⊕TZLBP)

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Abstract

In this paper, a novel feature descriptor named Z with Tilted Z Local Binary Pattern (Z⊕TZLBP) is proposed for extracting coral reef image features efficiently. The aim is to reduce LBP’s computational complexity by reducing the size of the feature vector. This is achieved in the proposed Z⊕TZLBP by dividing the neighborhood pixels into two non overlapped groups of Z and TZ (Tilted Z), and computing LBP wherein the centre pixel is also treated as one of the neighbors. KNN classification with four different distance metrices has been used for classification purpose. Metric F-measure is used to evaluate the performance of the proposed system. Experiments conducted with various coral image and video data sets show that the proposed feature descriptor outperforms Local Binary Pattern (LBP), Uniform Pattern, Center-Symmetric Local Binary Pattern and Orthogonal Combination of Local Binary Pattern and also guarantees accurate and efficient feature extraction.

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Acknowledgements

The authors would like to thank Oscar Beijbom for making MLC 2012 dataset publicly available on the web, ASM Shihavuddin for providing datasets such as EILAT, EILAT2, RSMAS, LAVA, KTH-Tips and UIUCTEX datasets and J.K.Patterson Edward for providing Suganthi Devadason Marine Research Institute (SDMRI) dataset.

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Correspondence to N. Ani Brown Mary.

Appendix

Appendix

To calculate the feature extraction using the proposed Z⊕TZLBP, consider a 3 \(\times\) 3 Block \(B_{k}\) in a coral image as shown below:

figure c
  • Step 1 The Z neighbors are identified using Eqs. (1518). Here, the Z neighbors are represented in blue color. Here, the centre pixel is treated as one of the neighbors.

    figure d
    $$D_{1} = 5 - 1 = 4$$
    $$D_{2} = 1 - 8 = - 7$$
    $$D_{3} = 8 - 2 = 6$$
    $$D_{4} = 2 - 3 = - 1$$
  • Step 2 The resultant of LBP for the Z group is given in Eq. (19).

    $$LBP\_Z = \left\langle {4, - 7, 6, - 1} \right\rangle$$
  • Step 3 The directional code for the Z neighbors is given by Eq. (20).

    $$Directional Code DC\_Z = \left\{ {1, 0, 1, 0} \right\}$$
  • Step 4 The directional codes of Z neighbors are converted into decimal values, the decimal values are summed together to form a feature vector, and is given by Eq. (21).

    $$1 \times 2^{0} = 1$$
    $$1 \times 2^{2} = 4$$
    $$DEC\_DC\_Z = 5$$
  • Step 5 The TZ neighbors are identified using Eqs. (22)–(25). Here, the TZ neighbors are represented in green color.

    figure e
    $$D_{1}^{{\prime }} = 9 - 11 = - 2$$
    $$D_{2}^{{\prime }} = 11 - 8 = 3$$
    $$D_{3}^{{\prime }} = 8 - 7 = 1$$
    $$D_{4}^{'} = 7 - 4 = 3$$
  • Step 6 The resultant of LBP for the TZ group is given in Eq. (26).

    $$LBP_{Z} = \left\langle { - 2, 3, 1, 3} \right\rangle$$
  • Step 7 The directional code for the TZ neighbors is given by Eq. (27).

    $$Directional\,Code DC\_Z = \left\{ {0, 1, 1, 1} \right\}$$
  • Step 8 The directional codes of TZ neighbors are converted into decimal values, the decimal values are summed together to form a feature vector, which is given by Eq. (28).

    $$1 \times 2^{1} = 2$$
    $$1 \times 2^{2} = 4$$
    $$1 \times 2^{3} = 8$$
    $$DEC\_DC\_Z = 14$$
  • Step 9 Feature Vector FV for a Block \(B_{k}\) is given by Eq. (29).

    $${\text{Feature}}\,{\text{Vector}}\,{\text{FV}} = \left\langle {5,14} \right\rangle$$

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Ani Brown Mary, N., Dejey, D. Classification of Coral Reef Submarine Images and Videos Using a Novel Z with Tilted Z Local Binary Pattern (Z⊕TZLBP). Wireless Pers Commun 98, 2427–2459 (2018). https://doi.org/10.1007/s11277-017-4981-x

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