Shape and surface measurement technology by an improved shape-from-shading neural algorithm

Siu-Yeung Cho; Tommy W. S. Chow

doi:10.1109/41.824148

Shape and surface measurement technology by an improved shape-from-shading neural algorithm

Siu-Yeung Cho, Tommy W. S. Chow

Department of Electrical Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

9 Citations (Scopus)

Abstract

A new approach for measuring the shape and surface of an object observed from a single camera is proposed. The proposed approach is based on using the neural networks as a parameteric representation of the three-dimensional object and the shape-from-shading problem is formulated as the minimization of an intensity error function with respect to the network weights. Experimental results demonstrate that our proposed methodology exhibits high efficiency and accuracy for measuring and inspecting the product's surface in the manufacturing industry.

Original language	English
Pages (from-to)	225-230
Journal	IEEE Transactions on Industrial Electronics
Volume	47
Issue number	1
DOIs	https://doi.org/10.1109/41.824148
Publication status	Published - Feb 2000

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access Output

10.1109/41.824148

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@article{1affc00681cf46dc8d32c6c7606f1137,

title = "Shape and surface measurement technology by an improved shape-from-shading neural algorithm",

abstract = "A new approach for measuring the shape and surface of an object observed from a single camera is proposed. The proposed approach is based on using the neural networks as a parameteric representation of the three-dimensional object and the shape-from-shading problem is formulated as the minimization of an intensity error function with respect to the network weights. Experimental results demonstrate that our proposed methodology exhibits high efficiency and accuracy for measuring and inspecting the product's surface in the manufacturing industry.",

author = "Siu-Yeung Cho and Chow, {Tommy W. S.}",

year = "2000",

month = feb,

doi = "10.1109/41.824148",

language = "English",

volume = "47",

pages = "225--230",

journal = "IEEE Transactions on Industrial Electronics",

issn = "0278-0046",

publisher = "IEEE Industrial Electronics Society",

number = "1",

}

TY - JOUR

T1 - Shape and surface measurement technology by an improved shape-from-shading neural algorithm

AU - Cho, Siu-Yeung

AU - Chow, Tommy W. S.

PY - 2000/2

Y1 - 2000/2

N2 - A new approach for measuring the shape and surface of an object observed from a single camera is proposed. The proposed approach is based on using the neural networks as a parameteric representation of the three-dimensional object and the shape-from-shading problem is formulated as the minimization of an intensity error function with respect to the network weights. Experimental results demonstrate that our proposed methodology exhibits high efficiency and accuracy for measuring and inspecting the product's surface in the manufacturing industry.

AB - A new approach for measuring the shape and surface of an object observed from a single camera is proposed. The proposed approach is based on using the neural networks as a parameteric representation of the three-dimensional object and the shape-from-shading problem is formulated as the minimization of an intensity error function with respect to the network weights. Experimental results demonstrate that our proposed methodology exhibits high efficiency and accuracy for measuring and inspecting the product's surface in the manufacturing industry.

UR - http://www.scopus.com/inward/record.url?scp=0034135574&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0034135574&origin=recordpage

U2 - 10.1109/41.824148

DO - 10.1109/41.824148

M3 - RGC 21 - Publication in refereed journal

SN - 0278-0046

VL - 47

SP - 225

EP - 230

JO - IEEE Transactions on Industrial Electronics

JF - IEEE Transactions on Industrial Electronics

IS - 1

ER -

Shape and surface measurement technology by an improved shape-from-shading neural algorithm

Abstract

UN SDGs

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this