Ref.:
Ms. No. PAAA-D-10-00062
Rotation Invariant Features for Color Texture Classification and Retrieval under Varying
Illumination
Pattern Analysis and Applications
Reviewer1Reviewer #1: All the major points seem to have been addressed - and in particular the
authors have made it clear that it is image not surface rotation that they are dealing with.
- No correction required.
Reviewer 2- :
Sl.No
Comments
Modification
Page NOs
1
In the Abstract, 'Rotation' should not be
capitalised and some slight grammatical
changes are required (e.g., 'The quaternion
representation of color is shown to be
effective, which treats color ...")
Correction done.
Grammatically corrected.
Page 1
2
There are still several grammatical and
stylistic problems:
Spacing page 1, line 19, col 2.
Grammar page 2, line 6, col 1.
Correction done.
Page 1 &2
3
In equation (2) the norm of L is
identically one. So is L the "normalised"
illumination vector? Surely the image
intensity (i.e., the amount of light energy
reflected from a Lambertian surface)
depends on the intensity of the illuminant
and the angles to that surface. Section 2.1
needs reworking to describe the correct
physics of the illumination process. It
clearly doesn't apply in the case of a
highly specular surface for example.
Yes. It is normalized
illumination vector.
Page 3
4
Section 2.2 should probably cite:
Reference is included.(16)
Page 2
Yes. It is Principal
component analysis. It is
corrected.
Page 4 Column 2 ,
paragraph 2.
Yes.
Ref: Kanan, C. & Cottrell,
G. W. “Robust
Classification of Objects,
-
5
6
Koen E.A. van de Sande, Theo Gevers, Cees
G.M. Snoek, "Evaluating Color Descriptors
for Object and Scene Recognition," IEEE
Transactions on Pattern Analysis and
Machine Intelligence, pp. 1582-1596,
September, 2010
In Section 2.3 do the authors mean
quaternion principal component analysis
when they refer to "quaternion principle
analysis"?
Is the LMS color space well known in the
general imaging community? Please reference
or define.
Faces, and Flowers Using
Natural Image Statistics”,
In: Proceedings of the IEEE
Conference on Computer
Vision and Pattern
Recognition (CVPR
2010),pp.2472-2479, 2010.
7
Section 2.4: The explanation of quaternion
rotation is not clear. Why is "(0, I_q)" a
3D vector?
8
Would the authors please disclose the "15
selected textures" or were they randomly
selected?
3 color channels form a 3D
Page 5
quaternion vector. Each
dimension corresponds to a
color channel.
Yes they are randomly
Page 8
selected to cover different
classes of materials.
Reviewer #3: All major points of concern in my initial review have been addressed sufficiently
in this revised version. Hence, I recommend to accept this manuscript.
- No correction required.