Detection of defects in formed sheet metal using medial axis transformation

Murmu, Naresh Chandra; Velgan, Roman

doi:10.1117/12.500529

Cited by 3 publications

(1 citation statement)

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“…In [ 14 ] a collection of algorithms for the analysis of textures is shown, but most of them are for the classification of patterns. The work in [ 15 ] deals with a method based on the evaluation of local wall thickness and other imperfections, such us creases, using a medial axis transformation.…”

Section: General Description Of the Algorithms For The Determination mentioning

confidence: 99%

Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image

Barber

Zwilling

Salichs

2014

Sensors

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Nowadays the automobile industry is becoming more and more demanding as far as quality is concerned. Within the wide variety of processes in which this quality must be ensured, those regarding the squeezing of the auto bodywork are especially important due to the fact that the quality of the resulting product is tested manually by experts, leading to inaccuracies of all types. In this paper, an algorithm is proposed for the automated evaluation of the imperfections in the sheets of the bodywork after the squeezing process. The algorithm processes the profile signals from a retroreflective image and characterizes an imperfection. It is based on a convergence criterion that follows the line of the maximum gradient of the imperfection and gives its geometrical characteristics as a result: maximum gradient, length, width, and area.

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Section: General Description Of the Algorithms For The Determination mentioning

confidence: 99%