1. Fast color texture recognition using chromaticity moments
Pattern Recognition Letters 21 (2000)
Presented by Waseem Khatri

2. Existing approaches to texture analysis
Statistical – Moments , Co-occurrence matrix
Model Based – Fractal, Stochastic models
Structural – Microtexture , Macrotexture , Morphology
Transform – Fourier , Wavelet , Gabor transforms
Limitations
Computationally Intensive
Cannot differentiate subtle variation in textures
Scaling and Rotation

3. CIE xy chromaticity diagram of an image
Proposed Method
CIE xy chromaticity diagram of an image
2D and 3D moments to characterize a given color image.
Classification using distance measure

4. CIE XYZ Color Space Chromaticity:
The quality of a color as determined by its dominant wavelength
Chromaticity diagram is a two dimensional representation of an image where each pixel produces a pair of (x,y) values
Matlab: rgb2xyz

5. 2D Shape and 2D distribution
2D Trace D Distribution

6. Moments Why moments ? Definition:
If f(x,y) is piecewise continuous and has non zero values only in a finite part of the xy-plane, moments of all orders exist and the moment sequence (mpq) is uniquely determined by f(x,y).
Why moments ?
Moments uniquely capture the nature of both the 2D shape and the 2D distribution of chromaticities.

7. Procedure Given image is converted into CIE xyz color space
The trace of the chromaticity diagram is computed
The 2D distribution is computed using:
D(x,y)= k , where k= #pixels producing (x,y)
Moments are computed using:
T(x,y) = if exists (i,j) : I(i,j) produces (x,y)
otherwise;
0<i<Lx , 0<i<Ly

8. Classification
Moments for all the classes in the database are computed
Moments for the test sample is computed
Minimum Distance measure
d=|x-xi| where x is the feature vector of the class
xi is the feature vector of the test image
The given test sample is assigned to the class from which it has the minimum distance

9. Conclusion Advantages Simple Efficient
Effective for a database with distinct texture
Uses small number of chromaticity moment features
Drawbacks
Error rate is high if the database contains textures that are not significantly different