Rough surface classification using point statistics from photometric stereo

Gerald McGunnigle; Mike Chantler

doi:10.1016/S0167-8655(00)00024-6

Rough surface classification using point statistics from photometric stereo

Gerald McGunnigle, Mike Chantler

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

Abstract

Rough surfaces can be classified by the point statistics of their derivative fields, estimated using photometric stereo. Such a scheme is proposed and found to be more accurate and robust than image-intensity-based classification. It is particularly effective when applied to directional surfaces, even under rotation. The scheme is therefore robust and economic - suitable for many applications and worthy of further investigation. © 2000 Elsevier Science B.V.

Original language	English
Pages (from-to)	593-604
Number of pages	12
Journal	Pattern Recognition Letters
Volume	21
Issue number	6-7
DOIs	https://doi.org/10.1016/S0167-8655(00)00024-6
Publication status	Published - Jun 2000

Keywords

Photometric stereo
Rotation invariance
Surface classification
Texture analysis

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10.1016/S0167-8655(00)00024-6

Cite this

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title = "Rough surface classification using point statistics from photometric stereo",

abstract = "Rough surfaces can be classified by the point statistics of their derivative fields, estimated using photometric stereo. Such a scheme is proposed and found to be more accurate and robust than image-intensity-based classification. It is particularly effective when applied to directional surfaces, even under rotation. The scheme is therefore robust and economic - suitable for many applications and worthy of further investigation. {\textcopyright} 2000 Elsevier Science B.V.",

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author = "Gerald McGunnigle and Mike Chantler",

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T1 - Rough surface classification using point statistics from photometric stereo

AU - McGunnigle, Gerald

AU - Chantler, Mike

PY - 2000/6

Y1 - 2000/6

N2 - Rough surfaces can be classified by the point statistics of their derivative fields, estimated using photometric stereo. Such a scheme is proposed and found to be more accurate and robust than image-intensity-based classification. It is particularly effective when applied to directional surfaces, even under rotation. The scheme is therefore robust and economic - suitable for many applications and worthy of further investigation. © 2000 Elsevier Science B.V.

AB - Rough surfaces can be classified by the point statistics of their derivative fields, estimated using photometric stereo. Such a scheme is proposed and found to be more accurate and robust than image-intensity-based classification. It is particularly effective when applied to directional surfaces, even under rotation. The scheme is therefore robust and economic - suitable for many applications and worthy of further investigation. © 2000 Elsevier Science B.V.

KW - Photometric stereo

KW - Rotation invariance

KW - Surface classification

KW - Texture analysis

UR - https://www.scopus.com/pages/publications/0033738319

U2 - 10.1016/S0167-8655(00)00024-6

DO - 10.1016/S0167-8655(00)00024-6

M3 - Article

SN - 0167-8655

VL - 21

SP - 593

EP - 604

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 6-7

ER -

Rough surface classification using point statistics from photometric stereo

Abstract

Keywords

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