Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30485
Title: Illumination-insensitive texture discrimination based on illumination compensation and enhancement
Authors: Jian, M
Lam, KM 
Dong, J
Keywords: Illumination compensation
Illumination enhancement
Illumination-effect matrix
Illumination-insensitive texture
Issue Date: 2014
Publisher: Elsevier
Source: Information sciences, 2014, v. 269, p. 60-72 How to cite?
Journal: Information sciences 
Abstract: As the appearance of a 3D surface texture is strongly dependent on the illumination direction, 3D surface-texture classification methods need to employ multiple training images captured under a variety of illumination conditions for each class. Texture images under different illumination conditions and directions still present a challenge for texture-image retrieval and classification. This paper proposes an efficient method for illumination- insensitive texture discrimination based on illumination compensation and enhancement. Features extracted from an illumination-compensated or -enhanced texture are insensitive to illumination variation; this can improve the performance for texture classification. The proposed scheme learns the average illumination-effect matrix for image representation under changing illumination so as to compensate or enhance images and to eliminate the effect of different and uneven illuminations while retaining the intrinsic properties of the surfaces. The advantage of our method is that the assumption of a single-point light source is not required, so it circumvents and overcomes the limitations of the Lambertian model and is also suitable for outdoor settings. We use a wide range of textures in the PhoTex database in our experiments to evaluate the performance of the proposed method. Experimental results demonstrate the effectiveness of our proposed methods.
URI: http://hdl.handle.net/10397/30485
ISSN: 0020-0255
EISSN: 1872-6291
DOI: 10.1016/j.ins.2014.01.019
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

8
Last Week
0
Last month
0
Citations as of Sep 10, 2017

WEB OF SCIENCETM
Citations

6
Last Week
0
Last month
Citations as of Sep 14, 2017

Page view(s)

46
Last Week
1
Last month
Checked on Sep 18, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.