Abaca Blend Fabric Classification Using Yolov8 Architecture
Advanced deep learning has assisted in various operations in different industries. In the textile industry, the professional must be trained and experienced in fabric classification. Fabrics such as Abaca are difficult to classify as the same base material is intertwined with a different material. T...
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MDPI AG
2025-04-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/92/1/42 |
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| author | Cedrick D. Cinco Leopoldo Malabanan R. Dominguez Jocelyn F. Villaverde |
| author_facet | Cedrick D. Cinco Leopoldo Malabanan R. Dominguez Jocelyn F. Villaverde |
| author_sort | Cedrick D. Cinco |
| collection | DOAJ |
| description | Advanced deep learning has assisted in various operations in different industries. In the textile industry, the professional must be trained and experienced in fabric classification. Fabrics such as Abaca are difficult to classify as the same base material is intertwined with a different material. The versatile nature of Abaca is used in various products including paper bills, ropes, handwoven handicrafts, and fabric. Abaca fabric is an unsought product of fabric due to its rough texture. Blended Abaca fabrics are traditionally mixed with cotton, silk, and polyester. Due to the combination of the characteristics of the materials, the fabric classification is prone to human error. Therefore, we created a device capable of classifying blends of Abaca fabric using YOLOv8 architecture. We used a Raspberry Pi 4B with camera module v3 to capture images for classification. The dataset consisted of four blends, specifically Abaca, Cotton Abaca, Polyester Abaca, and Silk Abaca. A total 500 images were used to test the model’s performance, and the performance accuracy was 94.6%. |
| format | Article |
| id | doaj-art-9c0f28dd6d0f4877bacde00af4a86ade |
| institution | OA Journals |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-9c0f28dd6d0f4877bacde00af4a86ade2025-08-20T02:20:57ZengMDPI AGEngineering Proceedings2673-45912025-04-019214210.3390/engproc2025092042Abaca Blend Fabric Classification Using Yolov8 ArchitectureCedrick D. Cinco0Leopoldo Malabanan R. Dominguez1Jocelyn F. Villaverde2School of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesSchool of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesSchool of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesAdvanced deep learning has assisted in various operations in different industries. In the textile industry, the professional must be trained and experienced in fabric classification. Fabrics such as Abaca are difficult to classify as the same base material is intertwined with a different material. The versatile nature of Abaca is used in various products including paper bills, ropes, handwoven handicrafts, and fabric. Abaca fabric is an unsought product of fabric due to its rough texture. Blended Abaca fabrics are traditionally mixed with cotton, silk, and polyester. Due to the combination of the characteristics of the materials, the fabric classification is prone to human error. Therefore, we created a device capable of classifying blends of Abaca fabric using YOLOv8 architecture. We used a Raspberry Pi 4B with camera module v3 to capture images for classification. The dataset consisted of four blends, specifically Abaca, Cotton Abaca, Polyester Abaca, and Silk Abaca. A total 500 images were used to test the model’s performance, and the performance accuracy was 94.6%.https://www.mdpi.com/2673-4591/92/1/42blended Abaca fabricYOLO8Raspberry PI4camera module v3fabric blend classification |
| spellingShingle | Cedrick D. Cinco Leopoldo Malabanan R. Dominguez Jocelyn F. Villaverde Abaca Blend Fabric Classification Using Yolov8 Architecture Engineering Proceedings blended Abaca fabric YOLO8 Raspberry PI4 camera module v3 fabric blend classification |
| title | Abaca Blend Fabric Classification Using Yolov8 Architecture |
| title_full | Abaca Blend Fabric Classification Using Yolov8 Architecture |
| title_fullStr | Abaca Blend Fabric Classification Using Yolov8 Architecture |
| title_full_unstemmed | Abaca Blend Fabric Classification Using Yolov8 Architecture |
| title_short | Abaca Blend Fabric Classification Using Yolov8 Architecture |
| title_sort | abaca blend fabric classification using yolov8 architecture |
| topic | blended Abaca fabric YOLO8 Raspberry PI4 camera module v3 fabric blend classification |
| url | https://www.mdpi.com/2673-4591/92/1/42 |
| work_keys_str_mv | AT cedrickdcinco abacablendfabricclassificationusingyolov8architecture AT leopoldomalabananrdominguez abacablendfabricclassificationusingyolov8architecture AT jocelynfvillaverde abacablendfabricclassificationusingyolov8architecture |