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首页> 外文会议>CAMP '95 : Computer architectures for machine perception >Low level Segmentation Using CMOS Smart Hexagonal Image Sensor
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Low level Segmentation Using CMOS Smart Hexagonal Image Sensor

机译：使用CMOS智能六角图像传感器进行低级分割

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摘要

The exploitation of analog VLSI techniques combined with computer vision knowledge offers spectacular possibilities. Limitations of current VLSI technologies do not allow to create sensors with extremely complex pixel architecture, but the coupling of external CMOS analog processing units is a great solution for rapid low level segmentation processes. This paper presents a novel sensing approach where photo-transduction, multiresolution feature extraction, scale-space integration, and edge tracking combined with sub-pixel interpolation are performed on a mixed-signal (digital - analog) VLSI architecture. The paper also discusses how we implement the curvature primal sketch into the system for higher level scene representation. The main sensory part of this integrated image acquisition system is a CMOS sensor called Multiport Access photo-Receptor (MAR). VLSI also provides means to integrate analog computing, digital controller, and DSP co-processor modules which define a powerful sensory chip set for focal plane image processing. A current version of the MAR sensor which implements 256 x 256 pixels includes 16 analog spatial filters which simultaneously compute multiresolution edge maps. This novel smart image sensor approach with associated low level segmentation capability presents good opportunities for real time automated process for the particular case of unstructured environment.
机译：模拟VLSI技术与计算机视觉知识的结合提供了惊人的可能性。当前VLSI技术的局限性不允许创建具有极其复杂的像素架构的传感器，但是外部CMOS模拟处理单元的耦合是快速进行低级分段处理的理想解决方案。本文提出了一种新颖的传感方法，其中在混合信号（数字-模拟）VLSI架构上执行了光转导，多分辨率特征提取，比例空间集成以及边缘跟踪与子像素插值相结合的操作。本文还讨论了如何将曲率原始草图实现到系统中以用于更高级别的场景表示。该集成图像采集系统的主要传感部分是称为多端口访问感光器（MAR）的CMOS传感器。 VLSI还提供了集成模拟计算，数字控制器和DSP协处理器模块的方法，这些模块定义了功能强大的传感芯片组，用于焦平面图像处理。可实现256 x 256像素的MAR传感器的当前版本包括16个模拟空间滤波器，可同时计算多分辨率边缘图。这种新颖的智能图像传感器方法具有关联的低级分割能力，为非结构化环境的特定情况提供了实时自动化过程的良好机会。

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  • 会议地点 Como(IT);Como(IT)
  • 作者

    Marc Tremblay; Stephane Dallaire; Denis Poussart;

  • 作者单位

    Computer Vision and Digital Systems Laboratory, Department of Electrical and Computer Engineering Laval University, Quebec, Canada, G1K 7P4;

    Computer Vision and Digital Systems Laboratory, Department of Electrical and Computer Engineering Laval University, Quebec, Canada, G1K 7P4;

    Computer Vision and Digital Systems Laboratory, Department of Electrical and Computer Engineering Laval University, Quebec, Canada, G1K 7P4;

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  • 正文语种 eng
  • 中图分类 总体结构、系统结构;
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