The paper briefly reviews certain aspects of the biological visual system and presents a smart vision sensor for the detection of higher-level features. The visual system processes information in a hierarchical manner starting from the retina up to the visual cortex. It decomposes the image in simple features (edges, orientation, line stops, corners, etc) using spatial and temporal information. At the higher level it integrates these primitive features, resulting in the recognition of complex objects. The sensor described in the paper is loosely modeled after the visual system and incorporates pixel level, programmable elements which extract orientation, end stops, corners and junctions from a line drawing. The architecture resembles a CNN-UM that can be programmed with a 30-bit word. The 16 x 16 pixels array detects these higher-level features in about 54 μseconds.
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机译：本文简要回顾了生物视觉系统的某些方面，并提出了一种用于检测高级特征的智能视觉传感器。视觉系统以分层的方式处理信息，从视网膜到视觉皮层。它使用空间和时间信息将图像分解为简单的特征（边缘，方向，直线停靠点，拐角等）。在较高级别上，它集成了这些原始功能，从而可以识别复杂的对象。本文中描述的传感器是在视觉系统之后进行松散建模的，并结合了像素级，可编程元素，这些元素可从线条图中提取方向，终点挡块，拐角和接合点。该架构类似于可以用30位字编程的CNN-UM。 16 x 16像素阵列可在约54微秒内检测到这些高级功能。
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