Integral Image Optimizations for Embedded Vision Applications
Integral Image Optimizations for Embedded Vision Applications
复制标题
嵌入式视觉应用的整体图像优化
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
B. Kisačanin
中科院分区：
文献类型：
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作者：
B. Kisačanin
本文阐述了算法和嵌入式软件技术的重要性，最佳的嵌入式实现的图像分析和计算机视觉功能：积分图像。在嵌入式处理器上简单、直接地实现积分映像可能会产生不可接受的执行时间。但是，通过应用递归和双缓冲，可以将执行时间提高几个数量级。我们比较了每种优化技术的执行时间和内存利用率。这些技术也可以应用于在可编程处理器架构上实现其他计算机视觉功能。
This paper illustrates the importance of both algorithmic and embedded software techniques for an optimal embedded implementation of an image analysis and computer vision function: the integral image. A naive, straightforward implementation of the integral image on an embedded processor will likely produce an unacceptable execution time. However, by applying recursion and double buffering, one can improve execution time by several orders of magnitude. We compare execution times and memory utilization for each of the optimization techniques applied. These techniques can also be applied to implement other computer vision functions on programmable processor architectures.