Abstract | ||
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A linear analog network model is proposed to describe the neural circuit of the outer retina. Using the model, we characterized the spatial filtering properties of the circuit in terms of the standard regularization theory in which the early vision problems are attributed to minimization of a cost function. Inspired by the algorithm/architecture of the circuit, a vision chip was designed using analog CMOS VLSI circuit technology. The chip fabricated is an one-dimensional 100 pixel line sensor. In the chip, sample/hold amplifier circuits are incorporated to compensate for the fixed pattern noise of photosensors as well as statistic transistor mismatch. The chip effectively extracts contour of given images by controlling the receptive field size, simulating a light-adaptive mechanism suggested in the vertebrate retinal circuit |
Year | DOI | Venue |
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1998 | 10.1109/KES.1998.726008 | Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference |
Keywords | Field | DocType |
CMOS analogue integrated circuits,CMOS image sensors,VLSI,analogue processing circuits,circuit optimisation,eye,physiological models,sample and hold circuits,spatial filters,100 pixel,analog CMOS VLSI circuit technology,analog VLSI,biological vision,circuit algorithm,circuit architecture,contour extraction,cost function minimization,early vision,fixed pattern noise,light-adaptive mechanism,line sensor,linear analog network model,neural circuit,outer retina,photosensors,receptive field size,sample/hold amplifier circuits,spatial filtering,standard regularization theory,statistic transistor mismatch,vertebrate retinal circuit,vision chip | Fixed-pattern noise,Computer vision,Vision chip,Computer science,Chip,Electronic engineering,Artificial intelligence,Electronic circuit,Transistor,Very-large-scale integration,Network model,Amplifier | Conference |
Volume | ISBN | Citations |
3 | 0-7803-4316-6 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Tetsuya Yagi | 1 | 140 | 27.73 |
Yuki Hayashida | 2 | 16 | 7.10 |
Seiji Kameda | 3 | 25 | 7.10 |