Automated cutting in the food industry using computer vision

Handle URI:
http://hdl.handle.net/10754/575834
Title:
Automated cutting in the food industry using computer vision
Authors:
Daley, Wayne D R; Arif, Omar
Abstract:
The processing of natural products has posed a significant problem to researchers and developers involved in the development of automation. The challenges have come from areas such as sensing, grasping and manipulation, as well as product-specific areas such as cutting and handling of meat products. Meat products are naturally variable and fixed automation is at its limit as far as its ability to accommodate these products. Intelligent automation systems (such as robots) are also challenged, mostly because of a lack of knowledge of the physical characteristic of the individual products. Machine vision has helped to address some of these shortcomings but underperforms in many situations. Developments in sensors, software and processing power are now offering capabilities that will help to make more of these problems tractable. In this chapter we will describe some of the developments that are underway in terms of computer vision for meat product applications, the problems they are addressing and potential future trends. © 2012 Woodhead Publishing Limited All rights reserved.
KAUST Department:
Visual Computing Center (VCC)
Publisher:
Elsevier BV
Journal:
Computer Vision Technology in the Food and Beverage Industries
Issue Date:
2012
DOI:
10.1533/9780857095770.2.206
Type:
Book Chapter
ISBN:
9780857090362
Appears in Collections:
Visual Computing Center (VCC); Book Chapters

Full metadata record

DC FieldValue Language
dc.contributor.authorDaley, Wayne D Ren
dc.contributor.authorArif, Omaren
dc.date.accessioned2015-08-24T09:54:48Zen
dc.date.available2015-08-24T09:54:48Zen
dc.date.issued2012en
dc.identifier.isbn9780857090362en
dc.identifier.doi10.1533/9780857095770.2.206en
dc.identifier.urihttp://hdl.handle.net/10754/575834en
dc.description.abstractThe processing of natural products has posed a significant problem to researchers and developers involved in the development of automation. The challenges have come from areas such as sensing, grasping and manipulation, as well as product-specific areas such as cutting and handling of meat products. Meat products are naturally variable and fixed automation is at its limit as far as its ability to accommodate these products. Intelligent automation systems (such as robots) are also challenged, mostly because of a lack of knowledge of the physical characteristic of the individual products. Machine vision has helped to address some of these shortcomings but underperforms in many situations. Developments in sensors, software and processing power are now offering capabilities that will help to make more of these problems tractable. In this chapter we will describe some of the developments that are underway in terms of computer vision for meat product applications, the problems they are addressing and potential future trends. © 2012 Woodhead Publishing Limited All rights reserved.en
dc.publisherElsevier BVen
dc.subjectAlgorithmsen
dc.subjectComputer visionen
dc.subjectInfrared (IR) sensorsen
dc.subjectMachine learningen
dc.subjectMachine visionen
dc.subjectVisible sensorsen
dc.subjectX-rayen
dc.titleAutomated cutting in the food industry using computer visionen
dc.typeBook Chapteren
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalComputer Vision Technology in the Food and Beverage Industriesen
dc.contributor.institutionGTRI/ATAS/FPTD, Georgia Institute of Technology, 640 Strong Street, Atlanta, GA 30332-0823, United Statesen
kaust.authorArif, Omaren
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