دورية أكاديمية

Detail texture detection based on Yolov4‐tiny combined with attention mechanism and bicubic interpolation

التفاصيل البيبلوغرافية
العنوان: Detail texture detection based on Yolov4‐tiny combined with attention mechanism and bicubic interpolation
المؤلفون: Tian Hui, YueLei Xu, Rasol Jarhinbek
المصدر: IET Image Processing, Vol 15, Iss 12, Pp 2736-2748 (2021)
بيانات النشر: Wiley, 2021.
سنة النشر: 2021
المجموعة: LCC:Computer software
مصطلحات موضوعية: Optical, image and video signal processing, Image recognition, Computer vision and image processing techniques, Photography, TR1-1050, Computer software, QA76.75-76.765
الوصف: Abstract Aero‐engine blades crack detection is one of the important tasks in daily ground maintenance, crack is a kind of texture feature, due to the random distribution, irregular shape and vague characteristics, which is still a challenging task to realize automatic detection in working environment. A detection model based on the Yolov4‐tiny is proposed that is universal and focuses more on the characteristics of cracks, and it is implemented in embedded device. First, in order to distinguish the cracks and noises, an improved attention module is introduced into the backbone of Yolov4‐tiny to enhance the model's capability to focus on crack areas; second, in order to improve the effect of multi‐scale feature fusion, the bicubic interpolation is implemented in upsampling module; finally, in order to solve the redundant detection results of bounding‐boxes in crack areas, the optimized non‐maximum suppression method is proposed to make the detection results better corresponding to the groundTruth. The robustness of proposed detection model was demonstrated by evaluating varying lighting and noise images. The average precision on integrated datasets is 81.6%, which outperforms the original Yolov4‐tiny by an increase of 12.3%.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1751-9667
1751-9659
Relation: https://doaj.org/toc/1751-9659; https://doaj.org/toc/1751-9667
DOI: 10.1049/ipr2.12228
URL الوصول: https://doaj.org/article/3be7dad4cb6342fba7eb0578fa93e84e
رقم الأكسشن: edsdoj.3be7dad4cb6342fba7eb0578fa93e84e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17519667
17519659
DOI:10.1049/ipr2.12228