• DocumentCode
    3197300
  • Title

    Focus measures for SFF-inspired relative depth estimation

  • Author

    Senthilnathan, R. ; Sivaramakrishnan, R.

  • Author_Institution
    Dept. of Production Technol., Anna Univ., Chennai, India
  • fYear
    2012
  • fDate
    14-15 Dec. 2012
  • Firstpage
    185
  • Lastpage
    188
  • Abstract
    Shape from Focus (SFF) is a method which recovers the 3D geometry of the scene based on a sequence of images taken from different focus distances between the camera and the object. Generally SFF techniques require parallel projection of the scene on to the image plane so that the corresponding pixels in the set of images taken are easily identified. This can be achieved by using a lens which does parallel projection such as a telecentric lens. Moreover the SFF method is widely applied for extremely small objects due to the limited range of magnification that can be maintained. This again is another manifestation of the fact depth of objects produce perspective shift (generally called as structure-dependent pixel motion) in the image plane. All these facts are applicable for situations which utilizes SFF for complete reconstruction of the scene. Applications involving shape information extracted from focus as a secondary cue need not require a complete dense reconstructed information from SFF. Such applications might allow usage of wide angle lenses where the projection is basically a perspective projection of the scene on to the image plane. The research work utilizes a wide angle lens for SFF based scene reconstruction consisting of a macroscopic object. The paper is an attempt to present 24 different focus measures used for quantifying image focus from which depth is interpolated using a standard function. Since the images in the sequence suffer from changes in magnification, finding the correspondence itself is an issue worth addressing. The pixel motion is tackled by a powerful corner detector and a robust matching algorithm. The knowledge of the right focus measure is very important since it is after all from the focus measure depth of the scene is interpolated. The focus measures presented in the paper are a collection from various applications such as microscopy imaging, auto focussing, holographic reconstructions etc., but applied to an image sequence conta- ning variations in focus and magnification.
  • Keywords
    computational geometry; feature extraction; image motion analysis; image reconstruction; image sequences; 3D geometry; SFF-inspired relative depth estimation; focus measures; image plane; image sequence; macroscopic object; parallel projection; scene reconstruction; shape from focus; shape information extraction; structure-dependent pixel motion; Artificial intelligence; Discrete cosine transforms; Histograms; Image edge detection; Manganese; Microscopy; Corner Detection; Focus Measures; Point Correspondences; SFF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Image Processing (MVIP), 2012 International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4673-2319-2
  • Type

    conf

  • DOI
    10.1109/MVIP.2012.6428791
  • Filename
    6428791