PIPE: A Parallel Processor For Dynamic Image Processing

1987 ◽  
Author(s):  
Randall L. Luck
Keyword(s):  
Image Processing ◽  
Parallel Processor ◽  
Dynamic Image

Driver-Car Communication Would Introduce a Drastic Change in Vehicle Design

2010 ◽  
Author(s):  
Shuichi Fukuda
Keyword(s):  
Image Processing ◽  
Driving Simulator ◽  
Processing Technique ◽  
Machine Design ◽  
Image Processing Technique ◽  
Dynamic Image ◽  
State Of Mind ◽  
Guidance Systems ◽  
Institute Of Technology ◽  
Technology Research Group

This paper discusses the potential role of emotion in changing our machine design, based upon the experiments conducted for about 20 years by TMIT (Tokyo Metropolitan Institute of Technology) research group headed by the author. An automobile design shares the same issues as those in our future machine design. In order to clarify these points, experiment to detect driver’s emotion were carried out. Our research to detect driver’s emotion started from the observations of a driver in driving, and based on them, experiments to detect driver’s emotion from face, sound and body were carried out. The following points were made clear. (1) a driving simulator is not good because a subject is in a different state of mind and physical conditions from actual driving. (2) Dynamic image processing is valid, but to make it effective, a simple image processing technique must be developed and a technique to remove lighting change effects must be developed. (3) When detecting from face, feature points must be carefully chosen. (4) Although sound is very promising, drivers do not utter voices often and if they do, their durations are very short. But if we introduce voice guidance systems, which would be much easier in EVs, detection from sound would work far more effectively than that from dynamic image, because images are very difficult to process due to the frequently changing lighting. (5) Physical movements can be used very effectively to detect fatigue. (6) Physical movement may be utilized for safer driving. If a new communication system between a driver and a car can be developed, the design of a car would change drastically. We do not have to, for example, use a wheel to steer. We could use bars. Equipments can be placed far away from the driver, if voice guidance systems can be introduced. Thus, a far greater degree of design flexibility could be introduced and a driver and a car could work better together as a team.

A Scalable Massively Parallel Processor for Real-Time Image Processing

2011 ◽  
Vol 46 (10) ◽  
pp. 2363-2373 ◽  
Author(s):  
Takashi Kurafuji ◽  
Masaru Haraguchi ◽  
Masami Nakajima ◽  
Tetsu Nishijima ◽  
Tetsushi Tanizaki ◽  
...  
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Massively Parallel ◽  
Parallel Processor ◽  
Real Time Image Processing ◽  
Real Time Image ◽  
Massively Parallel Processor ◽  
Time Image

Parallel processing in machine vision

Robotica ◽  
1984 ◽  
Vol 2 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Stanley R. Sternberg
Keyword(s):  
Image Processing ◽  
Parallel Processing ◽  
Machine Vision ◽  
Mathematical Morphology ◽  
Programming Language ◽  
Parallel Processor ◽  
Vision Systems ◽  
Processor Architectures ◽  
Image Flow ◽  
Industrial Part

SUMMARYMachine vision systems incorporating highly parallel processor architectures are reviewed. A new processor architecture, the image flow computer, is presented in detail. An interactive image processing programming language based on mathematical morphology is then presented. A detailed example of the use of the system for the inspection of a particular industrial part concludes the presentation.

Applications of remote image sensing with the NASA massively parallel processor

1988 ◽  
Vol 324 (1579) ◽  
pp. 365-372 ◽  
Keyword(s):  
Image Processing ◽  
Space Station ◽  
Image Data ◽  
General Purpose ◽  
Massively Parallel ◽  
Imaging Data ◽  
Parallel Processor ◽  
Image Sensing ◽  
Faint Object ◽  
Massively Parallel Processor

Satellite observing systems are producing image observations of the Earth’s surface and atmosphere with spectral and spatial resolutions that result in data rates that current general-purpose computing systems are incapable of processing and analysing. As a result, current processing systems have been able to analyse only limited amounts of image data with less than optimal algorithms for generating high-quality geophysical parameters. A massively parallel processor (mpp) is operationally available at NASA/GSFC for routine image-analysis applications. Research studies with the mpp are being pursued in the area of interactive spatial contextual classifications for the land thematic mapper data, automatic SIR-B stereo terrain mapping, icemotion detection, faint-object image restoration and other general purpose ocean and land image-processing systems. Several applications are presented comparing the mpp products with enhancements of imaging data with standard image-processing methods. Finally, a work-station parallel processor for space station on-board image processing will be described.

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