scholarly journals BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

2019 ◽  
Vol 9 (16) ◽  
pp. 3330 ◽  
Author(s):  
Patrick Dietrich ◽  
Stefan Heist ◽  
Martin Landmann ◽  
Peter Kühmstedt ◽  
Gunther Notni
Keyword(s):  
Real Time ◽  
High Speed ◽  
Cross Correlation ◽  
Stereo Matching ◽  
A Priori ◽  
Computer Hardware ◽  
Pattern Projection ◽  
Statistical Pattern ◽  
Image Area ◽  
Correspondence Search

Pattern projection-based 3D measurement systems are widely used for contactless, non-destructive optical 3D shape measurements. In addition, many robot-operated automation tasks require real-time reconstruction of accurate 3D data. In previous works, we have demonstrated 3D scanning based on statistical pattern projection-aided stereo matching between two cameras. One major advantage of this technology is that the actually projected patterns do not have to be known a priori in the reconstruction software. This allows much simpler projector designs and enables high-speed projection. However, to find corresponding pixels between cameras, it is necessary to search the best match amongst all pixels within the geometrically possible image area (that is, within a range on the corresponding epipolar line). The well-established method for this search is to compare each candidate pixel by temporal normalized cross correlation of the brightness value sequences of both pixels. This is computationally expensive and interdicts fast real-time applications on inexpensive computer hardware. We show two variants of our algorithm “Binary Correspondence Search” (BICOS), which solve this task in significantly reduced calculation time. In practice, our algorithm is much faster than traditional, purely cross-correlation-based search while maintaining a similar level of accuracy.

scholarly journals Robust surface matching by integrating edge segments

2014 ◽  
Vol II-5 ◽  
pp. 203-210
Author(s):  
N. Kochi ◽  
T. Sasaki ◽  
K. Kitamura ◽  
S. Kaneko
Keyword(s):  
High Precision ◽  
High Speed ◽  
Stereo Matching ◽  
Direct Consequence ◽  
Surface Matching ◽  
Matching Process ◽  
Edge Matching ◽  
Edge Surface ◽  
Image Area ◽  
Left Image

This paper describes a novel area-based stereo-matching method which aims at reconstructing the shape of objects robustly, correctly, with high precision and with high density. Our goal is to reconstruct correctly the shape of the object by comprising also edges as part of the resulting surface. For this purpose, we need to overcome the problem of how to reconstruct and describe shapes with steep and sharp edges. Area-based matching methods set an image area as a template and search the corresponding match. As a direct consequence of this approach, it becomes not possible to correctly reconstruct the shape around steep edges. Moreover, in the same regions, discontinuities and discrepancies of the shape between the left and right stereo-images increase the difficulties for the matching process. In order to overcome these problems, we propose in this paper the approach of reconstructing the shape of objects by embedding reliable edge line segments into the area-based matching process with parallax estimation. We propose a robust stereo-matching (the extended Edge TIN-LSM) method which integrates edges and which is able to cope with differences in right and left image shape, brightness changes and occlusions. The method consists of the following three steps: (1) parallax estimation, (2) edge-matching, (3) edge-surface matching. In this paper, we describe and explain in detail the process of parallax estimation and the area-based surface-matching with integrated edges; the performance of the proposed method is also validated. The main advantage of this new method is its ability to reconstruct with high precision a 3D model of an object from only two images (for ex. measurement of a tire with 0.14 mm accuracy), thus without the need of a large number of images. For this reason, this approach is intrinsically simple and high-speed.

scholarly journals Real-Time FPGA Accelerated Stereo Matching for Temporal Statistical Pattern Projector Systems

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6435
Author(s):  
Zan Brus ◽  
Marko Kos ◽  
Matic Erker ◽  
Iztok Kramberger
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Input Image ◽  
Stereo Image ◽  
Image Pair ◽  
Performance Per Watt ◽  
Statistical Pattern ◽  
And Performance ◽  
Image Pairs ◽  
High Level

The presented paper describes a hardware-accelerated field programmable gate array (FPGA)–based solution capable of real-time stereo matching for temporal statistical pattern projector systems. Modern 3D measurement systems have seen an increased use of temporal statistical pattern projectors as their active illumination source. The use of temporal statistical patterns in stereo vision systems includes the advantage of not requiring information about pattern characteristics, enabling a simplified projector design. Stereo-matching algorithms used in such systems rely on the locally unique temporal changes in brightness to establish a pixel correspondence between the stereo image pair. Finding the temporal correspondence between individual pixels in temporal image pairs is computationally expensive, requiring GPU-based solutions to achieve real-time calculation. By leveraging a high-level synthesis approach, matching cost simplification, and FPGA-specific design optimizations, an energy-efficient, high throughput stereo-matching solution was developed. The design is capable of calculating disparity images on a 1024 × 1024(@291 FPS) input image pair stream at 8.1 W on an embedded FPGA platform (ZC706). Several different design configurations were tested, evaluating device utilization, throughput, power consumption, and performance-per-watt. The average performance-per-watt of the FPGA solution was two times higher than in a GPU-based solution.

scholarly journals A Gist Warning of Sighting in Face Classification and Recognition

2019 ◽  
Vol 8 (4) ◽  
pp. 11166-11177
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Speed ◽  
Large Range ◽  
A Priori ◽  
Extraction Techniques ◽  
Face Classification ◽  
The Face ◽  
Real Time Applications ◽  
The Moment

Face classification and recognition is the fastest growing, challenging area in real time applications. A large number of algorithms are there in the network to recognize the face. It is the important part of the biometric traits and it not only contributes to the theoretical insights but also to practical insights of many algorithms. Conversely, the first face recognition in the main reckons on a priori in a row of hurdle folks and might not free itself from human intervention. Until the looks of high-speed, betterquality computers, the face recognition methodology makes a big disintegrate through. Face recognition has been a quick growing, difficult and mesmerizing space in real time applications. Facial classifications and recognition becomes an interesting research topic. A large range of face classification and recognition algorithms are developed in last decades. In this paper a attempt is created to review a good vary of strategies used for face recognition expansively. This paper contributes a huge survey of varied face detection and feature extraction techniques. At the moment, there are loads of face classification and recognition techniques and algorithms found and developed round the world.

Application of cross correlation to HREM images of surfaces

1987 ◽  
Vol 45 ◽  
pp. 754-755
Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett
Keyword(s):  
Cross Correlation ◽  
A Priori ◽  
Matrix Material ◽  
Correlation Method ◽  
Accurate Knowledge ◽  
Complex Image ◽  
Fourier Filtering ◽  
The Matrix ◽  
Low Pass ◽  
Data Reduction Technique

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.

High speed interferometric device for real-time correction of aero-optic effects

1995 ◽  
Author(s):  
Rod Clark ◽  
John Karpinsky ◽  
Gregg Borek ◽  
Eric Johnson
Keyword(s):  
Real Time ◽  
High Speed ◽  
Time Correction

Electrical Probing and Surface Imaging of Deep Sub-Micron Integrated Circuits

1999 ◽  
Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges
Keyword(s):  
High Resolution ◽  
Integrated Circuits ◽  
Real Time ◽  
High Speed ◽  
Time Signal ◽  
Surface Imaging ◽  
Atomic Force ◽  
Submicron Structures ◽  
High Resolution Images ◽  
Capacitive Loading

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.

Low-Cost High-Speed Techniques for Real-Time Simulation of Power Electronic Systems

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani
Keyword(s):  
Real Time ◽  
High Speed ◽  
Low Cost ◽  
Electronic Systems ◽  
Power Electronic ◽  
Real Time Simulation ◽  
Time Simulation
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