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17th International conference on machine vision applications (MVA)

作者： Wang, Hao Luo, Dingli Ikenaga, Takeshi Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9784901122207

3D pose estimation based on a monocular camera can be applied to various fields such as human-computer interaction and human action recognition. As a two-stage 3D pose estimator, videoPose3D achieves state-of-the-art accuracy. However, because of the limitation of two-stage processing, image information is partially lost in the process of mapping 2D poses to 3D space, which results in limited final accuracy. This paper proposes an image-assisting pose estimation model and a back-projection based offset generating module. The image-assisting pose estimation model consists of a 2D pose processing branch and an image processing branch. image information is processed to generate an offset to refine the intermediate 3D pose produced by the 2D pose processing network. The back-projection based offset generating module projects the intermediate 3D poses to 2D space and calculates the error between the projection and input 2D pose. With the error combining with extracted image feature, the neural network generates an offset to decrease the error. By evaluation, the accuracy on each action of Human3.6M dataset gets an average improvement of 0.9 mm over the videoPose3D baseline.

关键词： Human computer interaction Three-dimensional displays machine vision Pose estimation Neural networks Feature extraction Cameras

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Real-time image processing of TOF range images using a reconfigurable processor system

Real-time image processing of TOF range images using a recon...

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conference on videometrics, Range Imaging, and applications XI

作者： Hussmann, S. Knoll, F. Edeler, T. Westcoast Univ Appl Sci Inst Machine Vis Technol Ma Vi Tec D-25746 Heide Germany

ISBN: (纸本)9780819486813

During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in machine vision. In comparison to stereo vision system and laser range scanners they combine the advantages of active sensors providing accurate distance measurements and camera-based systems recording a 2D matrix at a high frame rate. Moreover low cost 3D imaging has the potential to open a wide field of additional applications and solutions in markets like consumer electronics, multimedia, digital photography, robotics and medical technologies. This paper focuses on the currently implemented 4-phase-shift algorithm in this type of sensors. The most time critical operation of the phase-shift algorithm is the arctangent function. In this paper a novel hardware implementation of the arctangent function using a reconfigurable processor system is presented and benchmarked against the state-of-the-art CORDIC arctangent algorithm. Experimental results show that the proposed algorithm is well suited for real-time processing of the range images of TOF cameras.

关键词： Phase measurement phase-shift algorithm photonic mixer devices (PMD) time-of-flight (TOF) optical distance measurement component real-time image processing instruction set interpretation custom instructions

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machine vision-Based Defect Detection in IC images Using the Partial Information Correlation Coefficient

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2013年第3期26卷 378-384页

作者： Wang, Chien-Chih Jiang, Bernard C. Lin, Jing-You Chu, Chien-Cheng Ming Chi Univ Technol New Taipei City Taiwan

The normalized cross correlation coefficient is a prevalent pattern-matching algorithm in machine vision for industrial inspections. Despite its common use, there are problems with practical applications. For instance, false alarms occur since it is highly sensitive to environmental changes or inspection equipment, not to mention it requires complex calculations. This paper proposes the partial information correlation coefficient (PICC) method to improve the traditional normalized cross correlation coefficient (TNCCC). The PICC uses the technique of significant points to calculate the correlation coefficient. An experiment is also conducted to demonstrate the application through many image samples from the IC industry, such as PCBs, BGAs, and ICs. The results show that the PICC can effectively reduce false alarms in defect detection.

关键词： Defect detection IC industry image processing pattern matching

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machine vision-based alignment: Space to factory to garage

Machine vision-based alignment: Space to factory to garage

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conference on machine vision applications, Architectures, and Systems Integration vi

作者： Christian, DJ Shroff, H SNAP ON DIAGNOST SAN JOSECA 95112

ISBN: (纸本)0819426377

machine vision is an enabling technology for many applications but ''alignment'' is arguably the most useful application class. Alignment is the task of ''finding the position of a landmark or work piece in the electronic image'' so that it can be tracked, moved, followed, or otherwise adjusted. Many early alignment applications were in aerospace and defense. The visual 'landmark' they used was a star, a constellation or a laser-designated target. These applications made possible highly stable satellite platforms, accurate antenna aiming, and accurate military ordinance that are simply not possible with any other technology. These 'aiming' applications were extensions of traditional gunsighting techniques and nautical navigation. In factory automation, vision-based alignment continues to play a key role in the semiconductor and electronics manufacturing revolution. Robotic machinery requires precision guidance to mate work pieces (dice and printed wiring boards) with process machinery (bonders, saws, and robots). machine vision technology arrived just in time to make this possible, and new developments continue to improve precision and productivity in this area. New alignment applications are emerging in unexpected areas, such as the automotive service garage. This paper describes a new automotive service application for vehicle wheel alignment. Two machine vision cameras measure the position and attitude of few: wheel-mounted targets as the vehicle rolls and is steered. Six axes of rotation are used to define locations and orientations of the axles in three dimensional space. Their values are visibly inferred and measured, and their geometric relationships computed. The measurements are compared against the vehicle's ideal design tolerances for adjustment and repair purposes.

关键词： machine vision computer vision alignment vision applications automotive

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Automatic generation of multipath algorithms in the cellular nonlinear network

Automatic generation of multipath algorithms in the cellular...

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conference on applications of Artificial Neural Networks in image processing vi

作者： Preciado, VM Guinea, D Montúfar, R Spanish Council Sci Res Inst Automat Ind Madrid 28500 Spain

ISBN: (纸本)0819439835

The traditional image processing techniques require a lot of computational effort due to data on each pixel are computed in a sequential way and the path of information is an A/D converter. The delay accumulation create in this process is unacceptable in real time image processing because of the high information flow managed in the usual vision tasks (e.g. automatic industrial inspection, vision problems in robotics, pattern analysis, etc.). Thus, the use of a massive parallel architecture working with analog signals avoids the previous problems. This is just the basis idea of Cellular Neural Network (CNN's): an array of analogic dynamic processors which cells interact directly within a finite local neighborhood. The local CNN connectivity allow its realization as VLSI chips that can operate at a very high speed and complexity. Nowadays CNN architectures implemented as VLSI chips shows the aptitude of extremely high speed compared with traditional digital image processing tools. The proliferation of more and more sophisticated CNN architectures, and the increasing effort to implant practical system based in CNN chips, make important the development of analog algorithm to perform complex image processing tasks dedicated to many different fields, i.e. industrial applications, robotic systems and pattern recognition. The objective of this work is to generate a learning machine capable of find solutions for complex image processing task by CNN's. First a general machine for automatic analog algorithm design independent of the problem to solve is created, this is accomplished through an evolutionary strategy that is an extension of genetic programming. Second, this work introduces a suite of sub-mechanisms that increase the power of genetic programming and contribute to reduce the enormous space search for producing a plentiful search. Some concepts in this section are related with AI theory, in such a way that in this work we are in the intersection field of AI and Imag

关键词： cellular neural network visual processing parallel computation peal time processing automatic templates generation genetic algorithms

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On Comparing Multiple Approaches for Classifying Vessels in imagery 6

On Comparing Multiple Approaches for Classifying Vessels in ...

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conference on Artificial Intelligence and machine Learning for Multi-Domain Operations applications vi

作者： Warner, John G. Patel, vishal M. US Naval Res Lab 4555 Overlook Ave SW Washington DC 20375 USA Johns Hopkins Univ Baltimore MD USA

ISBN: (纸本)9781510674219;9781510674202

Deep learning-based approaches, such as Convolutional Neural Nets (CNNs), have shown high performance in classifying contents of images. CNNs, however, have the notable drawbacks of potentially high computing costs, poor explainability, and wide performance variance if the underlying imagery data deviates from the training baseline. As advanced image processing capabilities are matured, the on-board detection of objects in space-based imagery is increasingly proposed. On-board satellite processing applications, which may be resource-limited, can drive the need for simpler models that reduce the necessary computing burden for edge computing applications. This raises the question of how well classic computer vision techniques can compete with more modern approaches. This paper characterizes and compares the performance of multiple computer vision models for the application of distinguishing maritime vessels from typical clutter in commercial electrooptical (EO) satellite imagery. A Support Vector machine (SVM) model using manually curated features is compared to multiple DL-based models spanning a range of model sizes, with the goal of determining whether classical approaches can compete favorably with DL when computational resources are taken into consideration. Differences in performance and processing resources are characterized between the approaches. Findings include that the SVM-based model may approach the accuracy of some CNN-based models for classifying images of clouds in satellite EO imagery for smaller DL-based models. However, even the smallest DL-based models, which take about the same computational resources as the SVM-based model, generally out-perform the SVMbased model. This finding may have implications for the operational use of on-board processing techniques for satellite payloads.

关键词： CNN spacecraft onboard processing Automatic Target Recognition maritime

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Computer vision and wavelet transforms

Computer vision and wavelet transforms

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4th conference on Wavelet applications

作者： Shi, QY Xu, CX Peking Univ. (China)

ISBN: (纸本)0819424935

This paper concentrates on how to construct wavelets according to the practical needs of computer vision and image processing. At first, a theory for the construction of dyadic wavelets has been established. The resulted dyadic wavelets possess zero-symmetric or zero-antisymmetric property, and can also be fastly decayed so that they are suitable for edge detection. Then an algebra approach for the construction of orthogonal wavelets is proposed. It facilitaes the selection of best wavelet for a given image processing task such as image compression.

关键词： Wavelets Wavelet transforms image compression Edge detection image processing Computer vision technology machine vision image quality Algorithms Electronic filtering

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machine vision image analysis capability for image intensifier tubes and systems

Machine vision image analysis capability for image intensifi...

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conference on Low-Light-Level and Real-Time Imaging Systems, Components and applications

作者： Alsman, D Paul, C Sartor, M USN Ctr Surface Warfare Crane Div Crane IN 47522 USA

ISBN: (纸本)0819445630

The image Intensifier Tube (IIT) is the most critical component within a night vision device. Acquisition, production, test and evaluation of image intensifier tubes can be greatly enhanced by the application of machine vision technology. The Navy, Air Force and Army have invested over $2,000,000 in the development of a machine vision-based test set known as the Automated Intensifier Measurement System (AIMS). This paper will describe methodologies employed in the AIMS to measure Modulation Transfer Function (MTF), Dark Spots, Bright Spots, Shear Distortion, and Gross Distortion.

关键词： Modulation transfer functions Calibration image intensifiers Distortion Promethium machine vision Detection and tracking algorithms image analysis image processing Photomasks

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Optics, Illumination, and image Sensing for machine vision vi

Optics, Illumination, and Image Sensing for Machine Vision V...

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Optics, Illumination, and image Sensing for machine vision vi

The conference materials contain 29 papers dealing with machine vision imaging. Illumination and sensing methods and systems, image and instrument models, optical processing, data manipulation, three-dimensional imagi... 详细信息

ISBN: (纸本)0819407518

关键词： Computer vision

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video Denoising using Temporal Coherency of video Frames and Sparse Representation 12

Video Denoising using Temporal Coherency of Video Frames and...

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12th Iranian/2nd International conference on machine vision and image processing, MviP 2022

作者： Torkashvand, Azadeh Behrad, Alireza Shahed University Electrical Engineering Department Tehran Iran

ISBN: (纸本)9781665412162

Sparse representation based on dictionary learning has been widely used in many applications over the past decade. In this article, a new method is proposed for removing noise from video images using sparse representation and a trained dictionary. To enhance the noise removal capability, the proposed method is combined with a block matching algorithm to take the advantage of the temporal dependency of video images and increase the quality of the output images. The simulations performed on different test data show the appropriate response of the proposed algorithm in terms of video image output quality. © 2022 IEEE.

关键词： image reconstruction

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