في هذا البحث، قمنا بمعالجة مصفوفة تعبر عن صورة اليد البشرية بغية الحصول
على مميزات هذه الصورة. في سبيل تحقيق ذلك، استخدمنا تقنية FPGA من خلال
تقسيم عمليات المعالجة إلى ثلاثة مسالك، يتم تنفيذها على التفرع. إذ ينفذ كل مسلك
باستخدام التقنية الأنبوبية بتقسيمه إلى ثلاثة مقاطع. بعد ذلك، عملنا على تقدير
التسريع الذي حصلنا عليه نتيجة استخدامنا للتقنية الأنبوبية و المسالك التفرعية.
و بالتالي، أصبح لدينا إمكانية تصميم نظام مضمن داخل شريحة، و استخدام الهواتف
النقالة كأجهزة متكاملة من ناحية الموارد المادية و البرمجية.
In this paper, we processed an array which represents the
human hand image to get the characteristics of this image. So,
we used FPGA technique, and the processing operation is
partitioned into three threads which is carried out in parallel.
Each thread is carried out using the pipeline technique by
partitioning thread into four segments. After that, we evaluated
the speedup that we get in result of using the pipeline technique
and the parallel threads. So, we have the possibility to design an
embedded system integrated into chip (SoC), and using the
mobile phones as integral devices support the software and
hardware resources.
References used
Oi Mean Foong, Tan Jung Low, Satrio Wibowo, “Hand Gesture Recognition: Sign to Voice System (S2V)”, International Journal of Electrical, Computer, and Systems Engineering 3:4, 2009
Tin Hninn Maung, “Real-Time Hand Tracking and Gesture Recognition System Using Neural Networks”, World Academy of Science, Engineering and Technology 50, 2009
Ming-Hsuan Yang, Narendra Ahuja, Mark Tabb, “Extraction of 2D Motion Trajectories and Its Application to Hand Gesture Recognition”, IEEE transactions on pattern analysis and machine intelligence, vol. 24, no. 8, august 2002
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