Title :
Real-time decision analysis-algorithms, architectures and implementation
Author :
Shung, C.B. ; Blanz, W.E. ; Petkovic, D.
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
Abstract :
Summary form only given, as follows. Decision analysis is the process of making an optimal decision (classification) based on extracted features as an input. Although an important task in supervised statistical pattern recognition, decision analysis is often the speed bottleneck of such a system. Most of the work on real-time pattern recognition was done in the area of feature extraction, and very little was done in the area of decision analysis. The design of a real-time decision analyzer that can operate at image sensor speeds is presented. The real-time performance is achieved by selecting a class of classifiers that is amenable to VLSI implementation and has considerable discriminatory power. A flexible system architecture for the decision analyzer is proposed. It can be tailored to particular user specifications and is based on a two-chip set as a building block. An application of the design to a low-level image segmentation system, called LISA, which is currently being built, is also reported
Keywords :
VLSI; computerised pattern recognition; computerised picture processing; real-time systems; LISA; VLSI; classification; feature extraction; image sensor speeds; low-level image segmentation system; optimal decision; real time decision analysis; real-time decision analyzer; real-time pattern recognition; real-time performance; supervised statistical pattern recognition; system architecture; Feature extraction; Image analysis; Image segmentation; Image sensors; Pattern analysis; Pattern recognition; Very large scale integration;
Conference_Titel :
Multidimensional Signal Processing Workshop, 1989., Sixth
Conference_Location :
Pacific Grove, CA
DOI :
10.1109/MDSP.1989.97033