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Serrano Arriezu, Luis Javier

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Serrano Arriezu

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Luis Javier

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Ingeniería Eléctrica, Electrónica y de Comunicación

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0000-0002-7072-4464

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494

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2021 - 20232
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Subject: Artificial intelligence ×

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    PublicationOpen Access
    Development and validation of an automatic and intelligent system for medullation and average diameter evaluation to alpaca, llama and mohair fibers
    (2021) Quispe Bonilla, Max David; Quispe Peña, Edgar; Serrano Arriezu, Luis Javier; Trigo Vilaseca, Jesús Daniel; Quispe Bonilla, Christian; Institute of Smart Cities - ISC
    The aim of this work was to develop and validate an automatic and intelligent system (based in artificial intelligence) capable of quantify and identify fibers, by type of medullation in 5 categories. This work was carried out in Lima, Peru. To develop the software a trained model was generated based on You Only Look at Once for medullation and DenseNet for average fiber diameter (AFD), using Python. Language C was used to develop the graphical user interface. For the hardware; mechanical, electronic and optical subsystems was design and development. Samples of white alpaca, llama and mohair fibers (2108, 1858, 901 fibers, respectively) were evaluated for identification the fibers medullation. Additionally, AFD of 197 samples of white alpacas were measured with two methods. This system identifies 5 types of medullation and measures the diameter of the fibers. Each sample is evaluated in 40 sec, considering about 1500 fibers/sample. At two-proportion z-test of different fiber medullation types obtained with direct counting and our system no significant differences were found. At t-test of AFD obtained with OFDA device and our system no significant difference were found. The relationship between these methods was very stronger (r=0.95). The use of this system is recommended for fiber evaluation for the purpose of genetic improvement of fibers in animal production; purchase-sale, and processing of fiber to verify the quality of fibers; and research on medullation to increase knowledge about alpaca, llama and mohair fibers.
  • Thumbnail Image
    PublicationOpen Access
    Development and validation of a smart system for medullation and diameter assessment of alpaca, llama and mohair fibres
    (Elsevier, 2023) Quispe Bonilla, Max David; Quispe Bonilla, Christian; Serrano Arriezu, Luis Javier; Trigo Vilaseca, Jesús Daniel; Bengoechea, J. J.; Quispe Peña, Edgar; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
    Medullated fibres, due to their higher resistance to bending and pressure, constitute a problem for the textile industry. Thus, having practical instruments to identify them is essential. Therefore, the aim of this research was to develop and validate a novel, swift, automatic system (referred to as S-Fiber Med) for medullation and diameter assessment of animal fibres based on artificial intelligence. The medullation of 88 samples of alpaca, llama and mohair fibres (41, 43 and 4, respectively) was evaluated. Additionally, 269 samples of alpacas were considered for average fibre diameter (AFD) and the results were compared with the Portable Fiber Tester (PFT) and Optical Fibre Diameter Analyser (OFDA) methods (72 and 197 samples, respectively). The preparation of each sample to be analysed followed the procedure described in IWTO-8-2011. Version 5 of “You Only Look Once” and DenseNet models were used to recognise the type of medullation and diameter of the fibres, respectively. Within each image (n = 661 for alpaca), all fibres were labelled (as Non-Medullated, Fragmented Medulla, Uncontinuous Medulla, Continuous Medulla and Strongly Medullated) using the LabelImg tool. Data augmentation technique was applied to obtain 3 966 images. Such data set was divided into 3 576 and 390 images for training and test data, respectively. For mohair samples (n = 321), a similar process was carried out. The data to train the model used to infer the diameter contained 16 446 fibres labelled with his respective AFD. A complementary hardware composed of three subsystems (mechanical, electronic, and optical) was developed for evaluation purposes. T-test, Pearson and Concordance correlation, Bland-Altman plot and linear regression analyses were used to validate and compare the S-Fiber Med with other methods. Results indicate that there was no significant difference between medullation percentage obtained with the projection microscope and the S-Fiber Med. The Pearson and Concordance correlation analysis shows a strong, high and significant relationship (P-value < 0.001). The AFDs of alpaca and llama fibre samples obtained with the two methods are very similar, because no significant difference was found at the t-test (P-value > 0.172), and they have a strong, high and significant relationship between them, given the high Pearson correlation value (r ≥ 0.96 with P-value < 0.001), high Concordance coefficient and bias correction factor. Similar results were found when PFT and OFDA100 were compared with S-Fiber Med. As a conclusion, this new system provides precise, accurate measurements of medullation and AFD in an expeditious fashion (40 seconds/sample).