Image-based Coral Reef Formation Detection and Change Assessment System

 
 
 
  • Abstract
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  • Abstract


    Coral reefs play an essential role in marine biodiversity as they provide protection and shelter for marine species. Coral reefs also take a major part in maintaining the amount of carbon dioxide and filtration of coastal waters. The destruction and decrease of coral reefs may lead to an imbalance in marine biodiversity. Hence, the coral reefs have to be protected through monitoring and surveillance.

    In this study, an image-based system that monitors coral reef formation detection and assess coral reef changes was implemented. Image Differencing and Post Classification Methods were used to perform detection and recognition of coral reef formation. Foreign objects such as coins, metal rod and stones were dropped to the experimental set-up. Significant changes in the coral reef environment as well as the significant changes in the formation of the coral reefs after the appearance of foreign objects were assessed. The average accuracy of the system relative to the foreign objects considered is 88.75%.

    Overall, the study proved that both algorithms are effective in underwater image processing of the coral reef formation. Statistically, there is no significant difference between the results of the two algorithms as used in this study in terms of recognition and detection.

     

     

     



  • Keywords


    Coral Reef; Image Differencing; Post Classification; Significant Change .

  • References


      [1] Hsiao YH, Chen CC, Lin SI, & Lin FP, “Real-world underwater fish recognition and identification, using sparse representation,” Ecol. Inform., vol. 23, (2014), pp. 13–21

      [2] Shiu YC & Ahmad S, “3D location of circular and spherical features by monocular model-based vision,” in Conference Proceedings., IEEE International Conference on Systems, Man and Cybernetics, (1989), pp. 576–581.

      [3] Ku KK, Bradbeer RS, Yeung LF, & Lam KY, “An underwater camera and instrumentation system for monitoring” in 11th IEEE International Conference on Mechatronics and Machine Vision in Practice, (2008), 10.1007/978-3-540-74027-8_13.

      [4] Bradbeer RS, Lam KKY, Yeung LF, & Ku KKK, “Real-time monitoring of fish activity on an inshore coral reef,” in Proceedings of MTS/IEEE OCEANS, (2005).

      [5] Negahdaripour S, Xu X, Khamenet A, & Gables C, “Applications of Direct 3D Motion Estimation for Underwater Machine Vision Systems,” in IEEE Oceanic Engineering Society. OCEANS’98. Conference Proceedings , (1998), pp. 51-55.

      [6] Soriano M, Marcos S, Saloma C, Quibilan M, and Alino P, “Image classification of coral reef components from underwater color video,” in MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295), vol. 2, (2001), pp. 1008–1013.

      [7] “Coral Reefs: Threats,” 2017. [Online]. Available: http://wwf.panda.org/our_work/oceans/coasts/coral_reefs/coral_threats/.

      [8] Ruangpayoongsak N, Sumroengrit J, and Leanglum M, “A floating waste scooper robot on water surface,” in International Conference on Control, Automation and Systems, (2017), pp. 1543–1548.


 

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Article ID: 27857
 
DOI: 10.14419/ijet.v7i4.16.27857




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