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Motion Detecting Artificial Retina Model by Two-Dimensional Multi-Layered Analog Electronic Circuits

Masashi KAWAGUCHI, Takashi JIMBO, Masayoshi UMENO

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Summary :

We propose herein a motion detection artificial vision model which uses analog electronic circuits. The proposed model is comprised of four layers. The first layer is a differentiation circuit of the large CR coefficient, and the second layer is a differentiation circuit of the small CR coefficient. Thus, the speed of the movement object is detected. The third layer is a difference circuit for detecting the movement direction, and the fourth layer is a multiple circuit for detecting pure motion output. When the object moves from left to right the model outputs a positive signal, and when the object moves from right to left the model outputs a negative signal. We first designed a one-dimensional model, which we later enhanced to obtain a two-dimensional model. The model was shown to be capable of detecting a movement object in the image. Using analog electronic circuits, the number of connections decrease and real-time processing becomes feasible. In addition, the proposed model offers excellent fault tolerance. Moreover, the proposed model can be used to detect two or more objects, which is advantageous for detection in an environment in which several objects are moving in multiple directions simultaneously. Thus, the proposed model allows practical, cheap movement sensors to be realized for applications such as the measurement of road traffic volume or counting the number of pedestrians in an area. From a technological viewpoint, the proposed model facilitates clarification of the mechanism of the biomedical vision system, which should enable design and simulation by an analog electric circuit for detecting the movement and speed of objects.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.2 pp.387-395
Publication Date
2003/02/01
Publicized
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DOI
Type of Manuscript
Special Section PAPER (Special Section on Analog Circuit Techniques and Related Topics)
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