A novel method to detect foreground region using morphological operations with block based enhancement for underwater images

  • Authors

    • M Sudhakar Research AssociateVITCC
    • M Janaki Meena Professor, VITCC
    2018-08-21
    https://doi.org/10.14419/ijet.v7i3.13159
  • Block-Based SSI, Foreground Extraction, Morphological Operations, Fuzzy Segmentation.

  • Abstract

    Automation of detecting the Foreground Region (FR) or Shape of the object is essential in several computer vision, object recognition applications and poses several challenges in case of underwater images. Although Synthetic Sonar Images produce better quality images scattering of light, color distortion and poor lighting conditions are the few characteristics that effects the natural scene of the captured image. A novel technique for extracting the foreground region from a low quality underwater image is presented in this paper. We have decomposed the image in to multiple levels based on discrete wavelet transforms (DWT) for improving the sharpness or to reduce the fogginess in the image in order to get the clear image. Subsequently, to determine the sharpness of the local patches in the image a block based SSI algorithm is presented. Finally, the segmentation is performed by computing the binary gradient mask with the Sobel edge detection algorithm along with morphological operations. The proposed method is fast, extracting the accurate foreground regions and also detect the smallest particles present in the image. The results are qualitatively compared with the improved fuzzy c-means clustering (FCM), Otsu’s Threshold and FCM thresholding by considering the static background images.

     

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  • How to Cite

    Sudhakar, M., & Janaki Meena, M. (2018). A novel method to detect foreground region using morphological operations with block based enhancement for underwater images. International Journal of Engineering & Technology, 7(3), 1751-1756. https://doi.org/10.14419/ijet.v7i3.13159

    Received date: 2018-05-22

    Accepted date: 2018-06-29

    Published date: 2018-08-21