2013
DOI: 10.1051/ijmqe/2013048
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Measurement of the perceived quality of a product

Abstract: Abstract. For some companies, visual inspection has become an essential step when seeking to improve the quality of their products. The aim of this control is to be sure of the perceived quality of the product, which often goes well beyond the quality expected by the customer. For this type of control, the controller should be able to detect any anomaly on a product, characterize this anomaly, and then evaluate it in order to decide if the product should be accepted or rejected. This paper describes how this c… Show more

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Cited by 4 publications
(2 citation statements)
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“…Aesthetic quality assessment is a complex task to perform [11], and manual inspection can suffer from poor interassessor reliability due to variances in attention, level of training, individual state (mood, sleep etc.) and more [12]. Therefore, aesthetic quality assessment can benefit from objective and automated systems which can minimize the human bias and make this procedure more objective.…”
Section: Defect Appearance and Quality Standardsmentioning
confidence: 99%
“…Aesthetic quality assessment is a complex task to perform [11], and manual inspection can suffer from poor interassessor reliability due to variances in attention, level of training, individual state (mood, sleep etc.) and more [12]. Therefore, aesthetic quality assessment can benefit from objective and automated systems which can minimize the human bias and make this procedure more objective.…”
Section: Defect Appearance and Quality Standardsmentioning
confidence: 99%
“…Visual defect detection requires inspecting units from various view angles given the non-constant relationship between illumination angle and the unit's surface for this task. Human defect detection entails: a) high labour cost and knowledge sharing between assessors and b) poor inter-assessor reliability [21]. A solution to these problems entails automation using machine vision piggybacked onto existing 3D metrology scans used for identifying geometrical deviations.…”
Section: Introductionmentioning
confidence: 99%