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Multimedia Tools and Applications

, Volume 78, Issue 24, pp 34513–34539 | Cite as

A structural based feature extraction for detecting the relation of hidden substructures in coral reef images

  • Mahmood SotoodehEmail author
  • Mohammad Reza Moosavi
  • Reza Boostani
Article
  • 62 Downloads

Abstract

In this paper, we present an efficient approach to extract local structural color texture features for classifying coral reef images. Two local texture descriptors are derived from this approach. The first one, based on Median Robust Extended Local Binary Pattern (MRELBP), is called Color MRELBP (CMRELBP). CMRELBP is very accurate and can capture the structural information from color texture images. To reduce the dimensionality of the feature vector, the second descriptor, co-occurrence CMRELBP (CCMRELBP) is introduced. It is constructed by applying the Integrative Co-occurrence Matrix (ICM) on the Color MRELBP images. This way we can detect and extract the relative relations between structural texture patterns. Moreover, we propose a multiscale LBP based approach with these two schemes to capture microstructure and macrostructure texture information. The experimental results on coral reef (EILAT, EILAT2, RSMAS, and MLC) and four well-known texture datasets (OUTEX, KTH-TIPS, CURET, and UIUCTEX) show that the proposed scheme is quite effective in designing an accurate, robust to noise, rotation and illumination invariant texture classification system. Moreover, it makes an admissible tradeoff between accuracy and number of features.

Keywords

Color texture descriptors Coral reef images Integrative co-occurrence matrix (ICM) Local binary pattern (LBP) Feature extraction Macrostructure texture information 

Notes

Acknowledgements

The authors of this paper express their deepest gratitude to the late Dr. Farshad Tajeripour, who paved the road for Mahmood Sotoodeh with unwavering support in the early stages of his Ph.D. thesis. We offer our deepest condolences to his family and know that God welcomes his soul to a heavenly place.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Mahmood Sotoodeh
    • 1
    • 2
    Email author
  • Mohammad Reza Moosavi
    • 1
  • Reza Boostani
    • 1
  1. 1.Department of Electrical and Computer EngineeringShiraz UniversityShirazIran
  2. 2.Department of Computer ScienceUtah State UniversityLoganUSA

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