Automation in quality monitoring of fabrics and garment seams

Gries, Thomas; Lutz, Volker; Niebel, Volker; Simonis, Kristina; Saggiomo, Marco

doi:10.1016/b978-0-08-101211-6.00014-8

Cited by 7 publications

(2 citation statements)

References 21 publications

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“…Classification techniques have also been used to categorize fabric and sewing defects in the industry using computer vision for different applications (e.g., see [39,40] for fabric defects and [41] for garment defects). It is interesting to note that the classification systems have also been employed in image retrieval systems.…”

Section: Research Backgroundmentioning

confidence: 99%

Garment Categorization Using Data Mining Techniques

Jain

Kumar

2020

Symmetry

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The apparel industry houses a huge amount and variety of data. At every step of the supply chain, data is collected and stored by each supply chain actor. This data, when used intelligently, can help with solving a good deal of problems for the industry. In this regard, this article is devoted to the application of data mining on the industry’s product data, i.e., data related to a garment, such as fabric, trim, print, shape, and form. The purpose of this article is to use data mining and symmetry-based learning techniques on product data to create a classification model that consists of two subsystems: (1) for predicting the garment category and (2) for predicting the garment sub-category. Classification techniques, such as Decision Trees, Naïve Bayes, Random Forest, and Bayesian Forest were applied to the ‘Deep Fashion’ open-source database. The data contain three garment categories, 50 garment sub-categories, and 1000 garment attributes. The two subsystems were first trained individually and then integrated using soft classification. It was observed that the performance of the random forest classifier was comparatively better, with an accuracy of 86%, 73%, 82%, and 90%, respectively, for the garment category, and sub-categories of upper body garment, lower body garment, and whole-body garment.

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Section: Research Backgroundmentioning

confidence: 99%

Garment Categorization Using Data Mining Techniques

Jain

Kumar

2020

Symmetry

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“…The mathematical methods for analysis, modeling and optimization are increasingly used in the sewing and textile technologies [1][2][3][4]. This allows avoiding the subjective factor and creates real conditions for automation of the processes.…”

Section: Introductionmentioning

confidence: 99%

Approximation of a function describing a quality criterion of the thermo-mechanical fusible interfacing process

Andonova¹,

Baeva²

2020

cdatp

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The present work aims to investigate the function describing the relationship between a quality criterion and input factors of the thermo-mechanical fusible /TMF/ interfacing process and to derive its effective approximation. An approximation by interpolation was applied for the purpose of the study. A numerical realization of a linear and exponential approximation of the mathematical model describing the TMF interfacing process was performed. An effective linear approximation of the function connecting the quality criterion with the input factors of the TMF interfacing process was found. This creates conditions for replacing the relatively complex function (describing the TMF interfacing process) with its linear approximation. The linear approximation gives the possibility easier and faster to determine the relationships between the input factors and the quality criterion. This created conditions for ignoring the subjective factor and for optimizing and automating the studied technological process.

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Measurements of a Finished Garment Using 3D Laser Image Processing

Dönmezer

2020

Lecture Notes in Mechanical Engineering

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Automation in quality monitoring of fabrics and garment seams

Cited by 7 publications

References 21 publications

Garment Categorization Using Data Mining Techniques

Garment Categorization Using Data Mining Techniques

Approximation of a function describing a quality criterion of the thermo-mechanical fusible interfacing process

Measurements of a Finished Garment Using 3D Laser Image Processing

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