• DocumentCode
    164737
  • Title

    Genetic algorithm for depth images in RGB-D cameras

  • Author

    Danciu, Gabriel ; Szekely, Iuliu

  • Author_Institution
    Dept. of Electron. & Comput., Univ. of Brasov, Braşov, Romania
  • fYear
    2014
  • fDate
    23-26 Oct. 2014
  • Firstpage
    233
  • Lastpage
    238
  • Abstract
    In this paper, a new method for unsupervised image segmentation that can be applied to RGB-D (red, green, blue - depth) cameras is presented. The method consists in using a genetic algorithm to optimize the homogeneity of the segmented regions of a depth image. It searches for the best gray level ranges for which the segmentation of the image is closer to the ground truth. Experimental results and comparisons to existing algorithms demonstrate how the proposed method works.
  • Keywords
    cameras; genetic algorithms; image segmentation; unsupervised learning; RGB-D cameras; depth images; genetic algorithm; gray level ranges; ground truth; homogeneity optimization; red-green-blue-depth cameras; unsupervised image segmentation; Algorithm design and analysis; Cameras; Cost function; Electronics packaging; Genetic algorithms; Histograms; Image segmentation; RGB-D camera; genetic algorithm; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design and Technology in Electronic Packaging (SIITME), 2014 IEEE 20th International Symposium for
  • Conference_Location
    Bucharest
  • Type

    conf

  • DOI
    10.1109/SIITME.2014.6967036
  • Filename
    6967036
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=164737