Massively Parallel Intelligent Preprocessing

大规模并行智能预处理

• 批准号: 13023205
• 负责人: YONEZU Hiroo
• 金额: $ 20.16万
• 依托单位: Toyohashi University of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research on Priority Areas
• 财政年份: 2000
• 资助国家: 日本
• 起止时间: 2000 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-13023205/
• 关键词: parallel networks; vision; biological retinas; analog LSI; edge-detection; motion-detection; motion detection; shape recognition; アナログ集積回路; 広ダイナミックレンジ; 局所適応; 特性ばらつき; 脳機能; 特徴抽出; オプティカルフロー; 超高集積回路

Real-time processing of moving images is ultimately hard in present time-sequential computer systems. Thus, we aimed to realize massively parallel pre-processing networks with low-power dissipation, based on the vision mechanisms of biological retinas and brains. Practically, analog LSIs have been tried to be developed, which detect the motion and recognize simple shapes of moving targets.In biological retinas and brains, the information on the edge of a target is extracted at an early stage. An edge-detection network was realized based on local adaptation and feedback to photoreceptors in vertebrate retinas. The edge was detected from an image with a wide brightness range of five orders of magnitude. The power dissipation was less by two orders of magnitude than that of vision chips under development with present technology.Then, a motion-detection network was developed based on the retinas and brains of locusts and flies, in which the edge signal was inputted. The speed of an approac … More hing target was detected. The time required, for the speed detection was shorter by one order of magnitude than that of present systems. A network for simple-shape recognition was developed based on the vision system of flogs. As a result, the simple shapes such as a circle, triangle and square were recognized. In these networks, a binary output and feedback circuit were adopted to suppress the wrong operation of analog circuits due to the mismatch of MOS transistors.It is predicted that a network for the motion detection of an approaching objects, combined with the simple-shape recognition, can be realized in a LSI. A curved motion consists of local direct-motion. Thus, a network was developed for a trace of motion of specific points of a target. Another motion-detection network was developed in which the motion of a background was suppressed. It is valuable for the collision avoidance of mobile vehicles. It is predicted that a time for the detection is reduced by 1/(number of pixels) (〜1/1000) when a massively parallel outputs are obtained without scanning. Less

在当前的时间序列计算机系统中，移动图像的实时处理是基于生物视网膜和大脑的视觉机制的预处理网络。提取目标的早期阶段。在带有预期学的芯片的芯片中，基于视网膜和果蝇开发了一个运动，在其中输入了边缘信号。通过当前系统的一个顺序，通过一个阶数，在这些网络中识别出一个简单的形状，例如圆形，三角形和正方形。 。输出无需扫描而获得。

项目成果

K.Nishio, H.Yonezu, M.Ohtani, H.Yamada, Y.Furukawa: "Analog Integrated Circuit for Motion Detection of Approaching Object Based on the Insect Visual System"Opt. Rev.. Vol.11-No.1. 38-47 (2004)

K.Nishio、H.Yonezu、M.Ohtani、H.Yamada、Y.Furukawa：“基于昆虫视觉系统的接近物体运动检测的模拟集成电路”选项。

K.Nishio, H.Yonezu, M.Ohtani, H.Yamada, Y.Furukawa: "Analog Metal-Oxide-Semiconductor Integrated Circuit Implementation of Approach Detection with Simple-Shape Recognition Based on Visual Systems of Lower Animals"Opt.Rev.. Vol.10,No.2. 96-105 (2003)

K.Nishio、H.Yonezu、M.Ohtani、H.Yamada、Y.Furukawa：“基于低等动物视觉系统的简单形状识别的接近检测的模拟金属氧化物半导体集成电路实现”Opt.Rev。

W.-C.Kim, J.-H.Kim, M.Lee, J.-K.Shin, H.Yonezu: "Biologically Motivated Active Vision System Using Artificial Retina Chip and Shape Memory Alloy Actuator"9th Int. Conf. on Neural Information Processing, Proceedings. 1356 (2002)

W.-C.Kim、J.-H.Kim、M.Lee、J.-K.Shin、H.Yonezu：“使用人工视网膜芯片和形状记忆合金执行器的生物驱动主动视觉系统”第 9 届 Int。

K.Nishio, H.Yonezu, M.Ohtani, H.Yamada, et al.: "Analog Network for Detection of Approaching Object with Shape Recognition Based on Visual Systems of Lower Animals"9th Int. Conf. on Neural Information Processing, Proceedings. 1428 (2002)

K.Nishio、H.Yonezu、M.Ohtani、H.Yamada 等人：“基于低等动物视觉系统的形状识别接近物体检测的模拟网络”第 9 期 Int。

M.Ohtani, H.Yamada, et al.: "Analog LSI Implementation of Biological Direction-Selective Neurons"Japanese Journal of Applied Physics. 41・3A. 1409-1416 (2002)

M.Ohtani、H.Yamada 等：“生物方向选择性神经元的模拟 LSI 实现”日本应用物理学杂志 41・3A 1409-1416 (2002)。