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Real-Time Signal Processing using Hardware Implementation of Bio-Inspired Systems

Real-Time Signal Processing using Hardware Implementation of Bio-Inspired Systems
使用仿生系统的硬件实现进行实时信号处理
批准号:
RGPIN-2014-04988
负责人:
Mirhassani, Mitra
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
预计视觉促进将在汽车安全、手持设备和无线成像方面发挥重要作用。与此同时,对成像系统降低功耗和面积的要求也在不断增加。因此,需要新的解决方案来实现这一目标。*传统的机器视觉系统必须对视野进行高速采样。它还必须为每一帧存储大量无用的信息,数据量在兆字节范围内。有用的信息被隐藏在每一帧的原始数据下,而这些原始数据又必须经过大量处理才能提取出来。*对于用于运动检测的图像传感器中的光流测量,处理任务更加复杂,因为光流既包括空间现象,也包括时间现象。这意味着用于光流测量的视觉系统必须被设计成测量时空信息,这需要大量的计算任务。*与传统的视觉系统不同,专用视觉芯片是一种同时包含图像采集和处理的集成电路。*在这项提案中,将研究具有并行像素阵列、使用模拟和混合信号结构芯片的先进集成视觉传感器。集成的传感器捕获并对图像进行预处理,这意味着它只会从每个像素中提取有用的数据。这些电路和算法的灵感来自昆虫视觉的生物学模型。*在昆虫中,眼睛元素具有类似于集成像素的二维拓扑。然而,昆虫的神经回路适应可变的光线,对探测运动物体很有用。集成的视觉传感器可以由模拟电路实现,而模拟电路又可以在低对比度环境中有效地工作。最重要的是,该方法允许将电路实现在一个小封装中,可以集成到复杂的系统中,作为智能传感器网络的预处理单元。
英文摘要
It is expected that vision facilitation will play an important part in automotive safety, handheld devices, and wireless imaging. At the same time demands on imaging systems to reduce power and area are increasing. Consequently, novel solutions are required to achieve this goal. * A conventional machine vision system has to sample a visual field at high speed. It also has to store large amounts of useless information, in the range of megabytes of data, for each frame. Useful information is buried under the raw data in each frame which, in turn, has to be heavily processed to extract it. * For optical flow measurement in image sensors used for motion detection, the processing task is even more complicated since optic flow is comprised of both spatial as well as temporal phenomena. This means that the vision system for optical flow measurement has to be designed to measure the spatio-temporal information, which requires a high number of computational tasks. * In contrast to conventional vision systems, a dedicated vision chip is an integrated circuit that contains both image acquisition and processing. * In this proposal, advanced integrated vision sensors with concurrent pixel arrays, using analog and mixed-signal structures chip will be investigated. The integrated sensor captures and pre-processes the image, which means it will extract only useful data from each pixel. The circuits and algorithms are inspired by biological models of insect vision. * In insects, the eye element has a 2-D topology that is similar to integrated pixels. However, the neural circuits in insects adapt to variable light and are useful for detecting moving objects. The integrated vision sensor can be implemented by analog circuits, which in turn can effectively function in low contrast environments. Most importantly, this method allows circuitry to be implemented in a small package, which can be integrated in complex systems, serving as a pre-processing unit for intelligent sensor networks.
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