Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective
Nowadays, people are more concerned about their skin conditions and are more willing to spend money and time on facial care routines. The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in...
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| Format: | Article |
| Language: | English |
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MMU Press
2024-06-01
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| Series: | Journal of Informatics and Web Engineering |
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| Online Access: | https://journals.mmupress.com/index.php/jiwe/article/view/796 |
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| author | Ying Huey Gan Shih Yin Ooi Ying Han Pang Yi Hong Tay Quan Fong Yeo |
| author_facet | Ying Huey Gan Shih Yin Ooi Ying Han Pang Yi Hong Tay Quan Fong Yeo |
| author_sort | Ying Huey Gan |
| collection | DOAJ |
| description | Nowadays, people are more concerned about their skin conditions and are more willing to spend money and time on facial care routines. The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. Those skin type readers in the beauty market are not applied well on Malaysian skin. Therefore, this paper proposes a facial skin analysis system tailored primarily for Malaysian skin. This paper integrated object detection and deep learning algorithms in developing skin-type readers. A unique dataset consisting solely of facial images of Malaysian skin was created from scratch for the model. Additionally, You Only Look Once version 5 (YOLOv5) is employed to detect users' facial skin conditions, such as acne, pigment, enlarged pores, uneven skin, blackheads, etc. Then, based on the detected skin conditions, it further classifies the user's skin type into the normal, oily, sensitive, or dry groups. |
| format | Article |
| id | doaj-art-917ff48332b446afbdc64e18388f4a40 |
| institution | OA Journals |
| issn | 2821-370X |
| language | English |
| publishDate | 2024-06-01 |
| publisher | MMU Press |
| record_format | Article |
| series | Journal of Informatics and Web Engineering |
| spelling | doaj-art-917ff48332b446afbdc64e18388f4a402025-08-20T02:20:58ZengMMU PressJournal of Informatics and Web Engineering2821-370X2024-06-013211810.33093/jiwe.2023.3.2.1795Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning PerspectiveYing Huey Gan0Shih Yin Ooi1https://orcid.org/0000-0002-3024-1011Ying Han Pang2Yi Hong Tay3Quan Fong Yeo4Public Mutual Berhad, MalaysiaMultimedia University, MalaysiaMultimedia University, Malaysia365 Production, MalaysiaMultimedia University, MalaysiaNowadays, people are more concerned about their skin conditions and are more willing to spend money and time on facial care routines. The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. Those skin type readers in the beauty market are not applied well on Malaysian skin. Therefore, this paper proposes a facial skin analysis system tailored primarily for Malaysian skin. This paper integrated object detection and deep learning algorithms in developing skin-type readers. A unique dataset consisting solely of facial images of Malaysian skin was created from scratch for the model. Additionally, You Only Look Once version 5 (YOLOv5) is employed to detect users' facial skin conditions, such as acne, pigment, enlarged pores, uneven skin, blackheads, etc. Then, based on the detected skin conditions, it further classifies the user's skin type into the normal, oily, sensitive, or dry groups.https://journals.mmupress.com/index.php/jiwe/article/view/796skin type classificationimage processingobject detectiondeep learningyolov5 |
| spellingShingle | Ying Huey Gan Shih Yin Ooi Ying Han Pang Yi Hong Tay Quan Fong Yeo Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective Journal of Informatics and Web Engineering skin type classification image processing object detection deep learning yolov5 |
| title | Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective |
| title_full | Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective |
| title_fullStr | Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective |
| title_full_unstemmed | Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective |
| title_short | Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective |
| title_sort | facial skin analysis in malaysians using yolov5 a deep learning perspective |
| topic | skin type classification image processing object detection deep learning yolov5 |
| url | https://journals.mmupress.com/index.php/jiwe/article/view/796 |
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