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A Dynamic Feature-Based Method for Hybrid BlurredMultiple Object Detection in Manufacturing Processes
المؤلف
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-05-31
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Vision-based inspection has been applied for quality control and product sorting in manufacturing processes.
Blurred or multiple objects are common causes of poor performance in conventional vision-based inspection systems.
Detecting hybrid blurred/multiple objects has long been a challenge in manufacturing.
For example, single-feature-based algorithms might fail to exactly extract features when concurrently detecting hybrid blurred/multiple objects.
Therefore, to resolve this problem, this study proposes a novel vision-based inspection algorithm that entails selecting a dynamic feature-based method on the basis of a multiclassifier of support vector machines (SVMs) for inspecting hybrid blurred/multiple object images.
The proposed algorithm dynamically selects suitable inspection schemes for classifying the hybrid images.
The inspection schemes include discrete wavelet transform, spherical wavelet transform, moment invariants, and edge-feature-descriptor-based classification methods.
The classification methods for single and multiple objects are adaptive region growing- (ARG-) based and local adaptive region growing- (LARG-) based learning approaches, respectively.
The experimental results demonstrate that the proposed algorithm can dynamically select suitable inspection schemes by applying a selection algorithm, which uses SVMs for classifying hybrid blurred/multiple object samples.
Moreover, the method applies suitable feature-based schemes on the basis of the classification results for employing the ARG/LARG-based method to inspect the hybrid objects.
The method improves conventional methods for inspecting hybrid blurred/multiple objects and achieves high recognition rates for that in manufacturing processes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lin, Tsun-Kuo. 2016. A Dynamic Feature-Based Method for Hybrid BlurredMultiple Object Detection in Manufacturing Processes. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112499
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lin, Tsun-Kuo. A Dynamic Feature-Based Method for Hybrid BlurredMultiple Object Detection in Manufacturing Processes. Mathematical Problems in Engineering No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1112499
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lin, Tsun-Kuo. A Dynamic Feature-Based Method for Hybrid BlurredMultiple Object Detection in Manufacturing Processes. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112499
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1112499
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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