Uniformly textured surfaces in 3D scenes provide important cues for image understanding. Texture can be used for both segmentation and for 3D shape inference. Unfortunately, virtually all current algorithms are based on assumptions that make it impossible to do texture segmentation and shape-from-texture in the same image. Texture segmentation algorithms rely on an absence of 3D effects that tend to distort the texture. Shape-from-texture algorithms depend on these effects, relying instead on the texture being already segmented. To really understand texture in images, texture segmentation and shape-from-texture must be viewed as a combined problem to be solved simultaneously. We present a solution to this problem with a region-growing algorithm that explicitly accounts for perspective distortions of otherwise uniform texture. We use the image spectrogram to compute local surface normals, which are in turn used to "frontalize" the texture. These frontalized texture patches are then subjected to a region-growing algorithm based on similarity in the local frequency domain and a minimum description length criteria. We show results of our algorithm on real texture images taken in the lab and outdoors.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Texture segmentation and shape in the same image


    Contributors:
    Krumm, J. (author) / Shafer, S.A. (author)


    Publication date :

    1995-01-01


    Size :

    672189 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Texture Segmentation and Shape in the Same Image

    Krumm, J. / Shafer, S. / IEEE Computer Society et al. | British Library Conference Proceedings | 1995


    Image Segmentation by Texture Analysis

    Di Ruberto, C. / Rodriguez, G. / Vitulano, S. et al. | British Library Conference Proceedings | 1999


    Affine Invariant Texture Segmentation and Shape from Texture by Variational Methods

    Ballester, C. / Gonzalez, M. | British Library Online Contents | 1998


    Image segmentation by texture analysis

    Di Ruberto, C. / Rodriguez, G. / Vitulano, S. | IEEE | 1999


    Contour and Texture Analysis for Image Segmentation

    Malik, J. / Belongie, S. / Leung, T. et al. | British Library Online Contents | 2001