於行動裝置上利用GPU平行運算實現FAST角點偵測演算法

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Title:	於行動裝置上利用GPU平行運算實現FAST角點偵測演算法
Other Titles:	Implementation of parallel computing FAST algorithm on mobile GPU
Authors:	吳臺宜;Wu, Tai-Yi
Contributors:	淡江大學電機工程學系碩士在職專班劉寅春
Keywords:	GPU平行運算;角點偵測;行動裝置;FAST演算法;GPU;FAST;SURF;Corner detection;Mobile Device;FAST Algorithm
Date:	2012
Issue Date:	2013-04-13 12:01:49 (UTC+8)
Abstract:	在影像處理中角點偵測是非常重要的一環，幾乎所有的應用都會用到，可以說角點偵測為影像辨識的根本之一。隨著行動裝置的普及，影像辨識也開始廣泛的應用到行動裝置上，然而礙於行動裝置硬體資源的缺乏和限制，要讓角點偵測可以在這些裝置上達到即時的處理是件很困難的一件工作。為了強化它的計算速度，我們使用了行動裝置上的GPU平行運算來加速FAST角點偵測演算法。根據實驗結果，透過GPU加速的FAST比一般版本快上了22.36倍，而相較於SURF演算法的角點偵測，更快上了448.5倍。 Corner detection is an extremely important technique in image recognition, which is widely employed in various applications for image recognition. With the widespread use of mobile devices, image recognition techniques are frequently applied in such devices. However, the hardware resource of smartphones are lacked and restricted, it is a difficult task to apply the techniques of corner detection smoothly in these devices. To enhance the computational speed, the FAST corner detection algorithm is implemented with parallel computing of GPU in mobile devices. In the experiments, the computational speed of the FAST corner detection algorithm increases 22.36 times after using GPU parallel computing. Compared with the widely known SURF algorithm, which is computed with mobile CPU only, the proposed technique in this study is 448.5 times faster than SURF algorithm.
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Thesis

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