论文信息 - A subjective-contour generation LSI system with expandable pixel-parallel architecture for vision systems

A subjective-contour generation LSI system with expandable pixel-parallel architecture for vision systems

Media processors that can be applied to vehicle or robot vision have been developed previously [1]. However, even using the latest media processors, the ability of artificial vision is far below that of human vision. All media processors are designed considering a trade-off between programmability (versatility) and performance, but low-level visual processing tasks are computationally intensive and fixed. Therefore, designing dedicated LSIs for such tasks are useful and cost-effective. The visual processing mechanisms in the brain are roughly illustrated as shown in Fig. 28.6.1. Since each part along the visual pathway in the brain has typical functions, developing dedicated LSIs for such functions is important. Ultimately, brain-like VLSI vision systems can be realized by combining such LSIs and digital media processors. The key to achieve brain-like artificial vision systems is the interaction between low- and high-level processing parts (e.g. V1-IT) by means of feedforward/feedback connections, and therefore massively parallel architecture and connectivity are essential for real-time operation.

Takashi Morie | Youngjae Kim

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