Engineering and Computer Science Faculty Publications
A New Perspective on Material Classification and Ink Identification
Document Type
Conference Proceeding
Publication Date
9-25-2014
Journal Title
2014 IEEE Conference on Computer Vision and Pattern Recognition
ISSN
1063-6919
DOI
10.1109/CVPR.2014.291
Abstract
The surface bi-directional reflectance distribution function (BRDF) can be used to distinguish different materials. The BRDFs of many real materials are near isotropic and can be approximated well by a 2D function. When the camera principal axis is coincident with the surface normal of the material sample, the captured BRDF slice is nearly 1D, which suffers from significant information loss. Thus, improvement in classification performance can be achieved by simply setting the camera at a slanted view to capture a larger portion of the BRDF domain. We further use a handheld flashlight camera to capture a 1D BRDF slice for material classification. This 1D slice captures important reflectance properties such as specular reflection and retro-reflectance. We apply these results on ink classification, which can be used in forensics and analyzing historical manuscripts. For the first time, we show that most of the inks on the market can be well distinguished by their reflectance properties.
Keywords
Ink, cameras, three-dimensional displays, accuracy, lighting, surface reconstruction, material classification, BRDF, ink identification
Recommended Citation
Shiradkar, Rakesh; Shen, Li; Landon, George V.; Ong, Sim Heng; and Tan, Ping, "A New Perspective on Material Classification and Ink Identification" (2014). Engineering and Computer Science Faculty Publications. 402.
https://digitalcommons.cedarville.edu/engineering_and_computer_science_publications/402
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
