於行動裝置上利用GPU平行運算實現FAST角點偵測演算法

Implementation of Parallel Computing FAST Algorithm on Mobile GPU

吳臺宜(Tai-Yi Wu)

指導教授 ： 劉寅春

共同指導教授 ： 周建興

淡江大學/工學院/電機工程學系碩士在職專班/碩士(2012年)

https://doi.org/10.6846/TKU.2012.00933

摘要

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。

關鍵字

GPU ； GPU平行運算 ； FAST ； SURF ； 角點偵測 ； 行動裝置 ； FAST演算法

並列摘要

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.

並列關鍵字

GPU ； FAST ； SURF ； Corner Detection ； Mobile Device ； FAST Algorithm

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