Real-Time Video Processing Using Native Programming on Android Platform
As the smartphone industry grows rapidly, smartphone applications need to be faster and real-time. For this purpose, most of the smartphone platforms run the program on the native language or compiler that can produce native code for hardware. However for the Android platform that based on the...
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Main Author: | |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2012
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Subjects: | |
Online Access: | http://eprints.utem.edu.my/id/eprint/4099/1/cspa_Real-Time_Video_Processing_Using_Native.pdf http://eprints.utem.edu.my/id/eprint/4099/ http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6194733&contentType=Conference+Publications&queryText%3DReal-Time+Video+Processing+Using+Native+Programming+on+Android+Platform |
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Summary: | As the smartphone industry grows rapidly,
smartphone applications need to be faster and real-time. For this
purpose, most of the smartphone platforms run the program on
the native language or compiler that can produce native code for
hardware. However for the Android platform that based on the
JAVA language, most of the software algorithm is running on
JAVA that consumes more time to be compiled. In this paper the
performance of native programming and high level
programming using JAVA are compared with respect to video
processing speed. Eight image processing methods are applied to
each frame of the video captured from a smartphone that is
running on an Android platform. The efficiencies of the two
applications with difference programming language are
compared by observing their frame processing rate. The
experimental results show that out of the eight images processing
methods, six methods that are executed using the native
programming are faster than that of the JAVA programming
with a total average ratio of 0.41. An application of the native
programming for real-time object detection is also presented in
this paper. The result shows that with native programming on
Android platform, even a complicated object detection algorithm
can be done in real-time. |
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