• DocumentCode
    595372
  • Title

    Depth image enhancement for Kinect using region growing and bilateral filter

  • Author

    Li Chen ; Hui Lin ; Shutao Li

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    3070
  • Lastpage
    3073
  • Abstract
    Microsoft´s Kinect as a recent 3D sensor has attracted considerable research attention in the fields of computer vision and pattern recognition. But its depth image suffers from the problem of poor accuracy caused by invalid pixels, noise and unmatched edges. In this paper, an efficient approach is proposed to improve the quality of Kinect´s depth image. Using its corresponding color image, the pixels with wrong depth values are detected and removed using a region growing method. To accurately estimate the values of invalid pixels, a joint bilateral filter is used to fill the holes. Considering the special noise property of Kinect sensor, an adaptive bilateral filter is proposed to effectively reduce the noise of the depth image. Experimental results show that the proposed method significantly improves the quality of depth image by successfully filling the holes, eliminating the unmatched edges and reducing the noise.
  • Keywords
    computer vision; edge detection; filtering theory; image colour analysis; image denoising; image enhancement; image resolution; image sensors; object detection; 3D sensor; Microsoft Kinect; adaptive bilateral filter; color image; computer vision; depth image enhancement; invalid pixel value estimation; noise reduction; pattern recognition; region bilateral filter; region growing filter; unmatched edge elimination; unmatched edges; wrong depth values; Color; Filling; Image color analysis; Image edge detection; Noise; Optical filters; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460813