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

Research output: Journal Publication › Article › 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
Number of pages	6
Journal	IEEE Transactions on Industrial Electronics
Volume	47
Issue number	1
DOIs	https://doi.org/10.1109/41.824148
Publication status	Published - Feb 2000
Externally published	Yes

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

UN SDGs

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

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10.1109/41.824148

Cite this

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

Abstract

ASJC Scopus subject areas

UN SDGs

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