NDLI: Extracting the shape and roughness of specular lobe objects using four light photometric stereo

Content Provider	IEEE Xplore Digital Library
Author	Solomon, F. Ikeuchi, K.
Copyright Year	1992
Description	Author affiliation: Robot Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA (Solomon, F.; Ikeuchi, K.)
Abstract	A noncontact method of measuring surface shape and surface roughness for part inspection is proposed. The method, called four-light photometric stereo, uses four lights that sequentially illuminate the object under inspection, and a video camera that takes images of the object. Conceptually, the problem has three parts: shape extraction, pixel segmentation, and roughness extraction. The shape information is produced directly by three-light and four-light photometric stereo methods. After shape information is obtained, statistical segmentation techniques can be applied to determine which pixels are specular and which are nonspecular. Then the specular pixels and shape information can be used, in conjunction with a simplified Torrance-Sparrow reflectance model, to determine the surface roughness. The method has successfully been applied to a number of synthetic and real objects.<>
Starting Page	466
Ending Page	471
File Size	523050
Page Count	6
File Format	PDF
ISBN	0818628553
ISSN	10636919
DOI	10.1109/CVPR.1992.223149
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-06-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Photometry Rough surfaces Surface roughness Shape measurement Stereo vision Inspection Reflectivity Data mining Manufacturing Light sources
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Extracting the shape and roughness of specular lobe objects using four light photometric stereo

Inspecting specular lobe objects using four light sources

Roughness and shape of specular lobe surfaces using photometric sampling method

Extracting the shape and roughness of specular lobe objects (1991).

Binocular Stereo Dense Matching in the Presence of Specular Reflections

Efficient photometric stereo on glossy surfaces with wide specular lobes

Determining shape and reflectance of Lambertian, specular, and hybrid surfaces using extended sources

Geometric and photometric constraints for surface recovery

Can two specular pixels calibrate photometric stereo?

Extracting the shape and roughness of specular lobe objects using four light photometric stereo

Similar Documents

Extracting the shape and roughness of specular lobe objects using four light photometric stereo

Inspecting specular lobe objects using four light sources

Roughness and shape of specular lobe surfaces using photometric sampling method

Extracting the shape and roughness of specular lobe objects (1991).

Binocular Stereo Dense Matching in the Presence of Specular Reflections

Efficient photometric stereo on glossy surfaces with wide specular lobes

Determining shape and reflectance of Lambertian, specular, and hybrid surfaces using extended sources

Geometric and photometric constraints for surface recovery

Can two specular pixels calibrate photometric stereo?

Extracting the shape and roughness of specular lobe objects using four light photometric stereo