Performance evaluation of wavelet scattering network in image texture classification in various color spaces

Texture plays an important role in many image analysis applications. In this paper, we give a performance evaluation of color texture classification by performing wavelet scattering network in various color spaces. Experimental results on the KTH_TIPS_COL database show that opponent RGB based wavelet scattering network outperforms other color spaces. Therefore, when dealing with the problem of color texture classification, opponent RGB based wavelet scattering network is recommended.

[1]  Stéphane Mallat,et al.  Generic Deep Networks with Wavelet Scattering , 2013, ICLR.

[2]  David Mumford,et al.  Communications on Pure and Applied Mathematics , 1989 .

[3]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[4]  S. Mallat,et al.  Invariant Scattering Convolution Networks , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Arnold W. M. Smeulders,et al.  Color Based Object Recognition , 1997, ICIAP.

[6]  Thomas Serre,et al.  A New Biologically Inspired Color Image Descriptor , 2012, ECCV.

[7]  Paul F. Whelan,et al.  Experiments in colour texture analysis , 2001, Pattern Recognit. Lett..

[8]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[9]  Vincent Lepetit,et al.  DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Koen E. A. van de Sande,et al.  Evaluating Color Descriptors for Object and Scene Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Stéphane Mallat,et al.  Group Invariant Scattering , 2011, ArXiv.

[12]  Stéphane Mallat,et al.  Invariant Scattering Convolution Networks , 2012, IEEE transactions on pattern analysis and machine intelligence.

[13]  Matti Pietikäinen,et al.  Classification with color and texture: jointly or separately? , 2004, Pattern Recognit..

[14]  Adrian Ford,et al.  Colour Space Conversions_1 , 1998 .