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Proceedings Paper

Optimization of image processing algorithms on mobile platforms
Author(s): Pramod Poudel; Mukul Shirvaikar
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Paper Abstract

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Paper Details

Date Published: 2 February 2011
PDF: 14 pages
Proc. SPIE 7871, Real-Time Image and Video Processing 2011, 787105 (2 February 2011); doi: 10.1117/12.876520
Show Author Affiliations
Pramod Poudel, The Univ. of Texas at Tyler (United States)
Mukul Shirvaikar, The Univ. of Texas at Tyler (United States)

Published in SPIE Proceedings Vol. 7871:
Real-Time Image and Video Processing 2011
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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