Real Time Large Depth Of Field 3-D Vision System

1988 ◽  
Author(s):  
Ghislain Begin
Keyword(s):  
Real Time ◽  
Vision System ◽  
Depth Of Field ◽  
Large Depth

Wavefront Coded Imaging Systems for MEMS Analysis

2002 ◽  
Author(s):  
Daniel L. Barton ◽  
Jeremy A. Walraven ◽  
Edward R. Dowski ◽  
Rainer Danz ◽  
Andreas Faulstich ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
High Performance ◽  
Imaging System ◽  
Three Dimensional ◽  
Imaging Systems ◽  
Depth Of Field ◽  
Real Time Imaging ◽  
Large Depth ◽  
Wavefront Coding

Abstract A new imaging technique called Wavefront Coding allows real-time imaging of three-dimensional structures over a very large depth. Wavefront Coding systems combine aspheric optics and signal processing to achieve depth of fields ten or more times greater than that possible with traditional imaging systems. Understanding the relationships between traditional and modern imaging system design through Wavefront Coding is very challenging. In high performance imaging systems nearly all aspects of the system that could reduce image quality are carefully controlled. Modifying the optics and using signal processing can increase the amount of image information that can be recorded by microscopes. For a number of applications this increase in information can allow a single image to be used where a number of images taken at different object planes had been used before. Having very large depth of field and real-time imaging capability means that very deep structures such as surface micromachined MEMS can be clearly imaged with one image, greatly simplifying defect and failure analysis.

scholarly journals Data integration by two-sensors in a LEAP-based Virtual Glove for human-system interaction

2021 ◽  
Author(s):  
Giuseppe Placidi ◽  
Danilo Avola ◽  
Luigi Cinque ◽  
Matteo Polsinelli ◽  
Eleni Theodoridou ◽  
...  
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Vision System ◽  
Hand Tracking ◽  
Selection Strategy ◽  
Motion Sensors ◽  
Leap Motion ◽  
Time Data ◽  
Lower Velocity ◽  
Human System

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.

scholarly journals A real-time machine-vision system for monitoring the textile raising process

2005 ◽  
Vol 56 (8-9) ◽  
pp. 831-842 ◽  
Author(s):  
Monica Carfagni ◽  
Rocco Furferi ◽  
Lapo Governi
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Vision System ◽  
Machine Vision System ◽  
Time Machine

VCS-IV: A real-time vision system using a digital vision chip

2006 ◽  
Vol 89 (6) ◽  
pp. 34-43 ◽  
Author(s):  
Shingo Kagami ◽  
Takashi Komuro ◽  
Yoshihiro Watanabe ◽  
Masatoshi Ishikawa
Keyword(s):  
Real Time ◽  
Vision System ◽  
Vision Chip
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