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Richard A. Fundakowski

dblp:76/9703 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1983
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Multimedia analysis and retrieval › image analysis › visual inspection
surface defect detection
0.011983
A Real-Time Automated Visual Inspection System for Hot Steel Slabs · IEEE Trans. Pattern Anal. Mach. Intell. 1983
Multimedia analysis and retrieval › image analysis
visual inspection
0.011983
A Real-Time Automated Visual Inspection System for Hot Steel Slabs · IEEE Trans. Pattern Anal. Mach. Intell. 1983
Embedded and real-time systems › real-time signal processing
real-time image processing
0.011983
A Real-Time Automated Visual Inspection System for Hot Steel Slabs · IEEE Trans. Pattern Anal. Mach. Intell. 1983

Methods — techniques the papers use, named apart from their topics

syntactic/semantic classification · 0.0statistical classification · 0.0array processor · 0.0
YearPublicationVenuePosition
1983 A Real-Time Automated Visual Inspection System for Hot Steel Slabs
abstract
This paper describes an inspection system designed to automatically detect and classify surface imperfections occurring on continuously cast hot steel slabs in a steel mill. The need to perform inspection at real-time throughput rates of 546 Kpixels/s using off-the-shelf components has led to the development of a unique architecture and algorithm set. The segmentation operations are done in a high-speed array processor front end. The imperfection classification is done in a mini-computer which uses statistical as well as syntactic/semantic classification techniques. The inspection system is currently undergoing evaluation in a steel mill.
Bindinganavle R. Suresh, Richard A. Fundakowski, Tod S. Levitt, John E. Overland
IEEE Trans. Pattern Anal. Mach. Intell.2