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نوع الوثيقة : مقال في مجلة دورية 
عنوان الوثيقة :
Moment Feature Based Fast Feature Extraction Algorithm for Moving Object Detection Using Aerial Images
Moment Feature Based Fast Feature Extraction Algorithm for Moving Object Detection Using Aerial Images
 
الموضوع : علوم حاسبات 
لغة الوثيقة : الانجليزية 
المستخلص : Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology. 
ردمد : 1932-6203 
اسم الدورية : PLOS One 
المجلد : 10 
العدد : 16 
سنة النشر : 1436 هـ
2015 م 
نوع المقالة : مقالة علمية 
تاريخ الاضافة على الموقع : Tuesday, March 8, 2016 

الباحثون

اسم الباحث (عربي)اسم الباحث (انجليزي)نوع الباحثالمرتبة العلميةالبريد الالكتروني
Anton Satria PrabuwonoSatria Prabuwono, Anton باحثدكتوراهantonsatria@eu4m.eu

الملفات

اسم الملفالنوعالوصف
 38356.pdf pdf 

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