author	bibliography	title
[Gerardo M. Chávez-Campos; Oscar D. Prieto; Enrique Reyes-Archundia; Héctor Javier-Vergara; Octavio Vázquez-Gómez; José A. Gutiérrez-Gnecchi]	[referenciasProtocoloPhD.bib]	A new Approach to Measuring the Decarburization Depth using an Image Segmentation Plugin

Introduction

Now a days, the high-temperature steel products are crucial for automotive, energy and aviation industries [@Lu2018]. This products improve their final properties through a reheating operation [@Ta2018]. The reheating operation is typically done on direct-fired furnaces where steelworks gases are combusted with excess air [@Young2016; @Korousic1996; @Gouveia2013].

The high-temperature, gas atmosphere and steel's chemistry lead to oxidation and decarburization of the steel [@Gouveia2013; @Tao2014; @Young2016]. Specifically, the decarburization is defined as the diffusion mechanism of the metal's carbon from the inner to outer zone replacing the lost carbon during the redox [@Young2016]; however, the decarburization becomes greater at high-temperature [@Gouveia2013]. Therefore, a none controlled reheating operation will produce material losses and depreciation on product quality [@Liu2018Numerical]. Then, a common way to establish the final product quality is by measuring the coating or decarburated layer [@Liu2018Numerical; @Alvarenga2015; @Zhao2016a]. This has be done by several methods and systems mainly validated by optical microscope (OM) techniques [@Tao2014; @Suarez2008; @Zhao2016a]. Nevertheless, the optical measurement-data were only based in few representative data; no more than five measurements [@Chen2020].

The E1077-01 "Standard Test Methods for Estimating the Depth of Decarburization of Steel Specimens". Proposes to make a number of random measurements around the specimen periphery, at randomly selected locations. If statistical precision is required, it suggests considering 95% of confident limits, mean and standard deviation; letting the number of measurements open, according to the desired accuracy. Thus, the present paper introduces a new approach to measure the decarburization depth based on image processing analysis.