Presentation 2005-10-20
A Psychologically-Inspired VLSI Brain Model System for Human-Like Image Recognition
Tadashi SHIBATA,
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Abstract(in English) A psychologically-inspired VLSI brain model has been developed to perform human-like flexible information processing. The system stores a vast quantity of past experience in the on-chip memory and the most relevant event in the past is automatically recalled in an immediate response to the current input. Since the search is carried out by a fully parallel processing on the chip, the response is extremely fast. In order to carry out human-like image recognition using the system, an edge-based image representation algorithm called Projected Principal-Edge Distribution (PPED) has been developed. It represents a two-dimensional image by a feature vector that very well preserves the human perception of similarity of images in the vector space, thus allowing us to perform robust image classification. The application of the system to handwritten pattern recognition, medical radiograph analysis, and face detection are presented as illustrative examples. Since the PPED vector generation is a computationally very expensive processing, a dedicated vector-generation VLSI processor employing mixed-signal architecture has been developed aiming at real time applications.
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Keyword(in English) VLSI / analog VLSI / digital processor / image processing / image recognition / vector quantization / psychological brain model / soft computing
Paper # SIP2005-109,ICD2005-128,IE2005-73
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Committee ICD
Conference Date 2005/10/13(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Psychologically-Inspired VLSI Brain Model System for Human-Like Image Recognition
Sub Title (in English)
Keyword(1) VLSI
Keyword(2) analog VLSI
Keyword(3) digital processor
Keyword(4) image processing
Keyword(5) image recognition
Keyword(6) vector quantization
Keyword(7) psychological brain model
Keyword(8) soft computing
1st Author's Name Tadashi SHIBATA
1st Author's Affiliation Department of Frontier Informatics, School of Frontier Science, The University of Tokyo()
Date 2005-10-20
Paper # SIP2005-109,ICD2005-128,IE2005-73
Volume (vol) vol.105
Number (no) 351
Page pp.pp.-
#Pages 9
Date of Issue