OpenCV在TI 達(dá)芬奇以及OMAP平臺(tái)下的移植與性能評(píng)估 In today’s advancing market, the growing performance and decreasing price of embedded processors are opening many doors for developers to design highly sophisticated solutions for different end applications. The complexities of these systems can create bottlenecks for developers in the form of longer development times, more complicated development environments and issues with application stability and quality. Developers can address these problems using sophisticated software packages such as OpenCV, but migrating this software to embedded platforms poses its own set of challenges. This paper will review how to mitigate some of these issues, including C++ implementation, memory constraints, floating-point support and opportunities to maximize performance using vendor-optimized libraries and integrated accelerators or co-processors. Finally, we will introduce a new effort by Texas Instruments (TI) to optimize vision systems by running OpenCV on the C6000? digital signal processor (DSP) architecture. Benchmarks will show the advantage of using the DSP by comparing the performance of a DSP+ARM? system-on-chip (SoC) processor against an ARM-only device.