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Improvement of Data-Driven 3-D Surface Quality Inspection by Deformation Simulation

Improvement of Data-Driven 3-D Surface Quality Inspection by...

引用

IEEE International conference on signal and image processing applications (IEEE ICSIPA)

作者： von Enzberg, Sebastian Al-Hamadi, Ayoub Fraunhofer Inst Mechatron Syst Design IEM Paderborn Germany Otto von Guericke Univ Inst Informat Technol & Commun IIKT Magdeburg Germany

ISBN: (纸本)9781728133775

The automated visual inspection of complexly shaped, stamped sheet metal is a challenging task. Model-based methods are currently state of the art for surface quality inspection based on three-dimensional surface measurements. Data-driven models allow the representation of arbitrary three-dimensional surface shapes including possible tolerances and variation due to deformation. Providing a sufficient amount of training data while ensuring adequate data quality is a time-consuming and laborous process. We propose a data driven three-dimensional surface model for quality inspection that allows the integration of deformation simulation in order to increase variance in training data. The effects of simulated data to the model quality are evaluated and results are given for data sets of automobile sheet metal parts.

关键词： 3-D signal processing surface quality inspection data-driven modelling

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Protecting Secret Data using RDE and Fuzzy Logic to Specify the Embedding Level

Protecting Secret Data using RDE and Fuzzy Logic to Specify ...

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IEEE International conference on signal and image processing applications (IEEE ICSIPA)

作者： Ilham, Ahmad Juniar Bawa, Putu Harum Ahmad, Tohari Inst Teknol Sepuluh Nopember Dept Informat Kampus ITS Surabaya Indonesia PT Bukalapakcom Software Engineer Jakarta Indonesia

ISBN: (纸本)9781728133775

Along with the rapid increase in information technology, there is a challenge in data security. For this reason, data protection has been a focus for some decades. One of the methods, called data hiding, is introduced to solve this security issue. It can protect secret data;nevertheless, the quality of the resulted stego data for a certain amount of the secret is limited. Moreover, the reversibility of the algorithm is also a concern. In this research, we intend to improve the method by combining Reduced Difference Expansion (RDE) and the concept of fuzzy logic, by considering some factors, such as brightness and its entropy value. It is to specify the number of embedding, which should be done for each block in an image. Therefore, the embedding level is dynamic, which means that it may be different for each block. The experimental result shows that this proposed method works well;adaptive such that it follows the characteristics of the carrier. Moreover, the method is also reversible that both the secret data and the carrier can be successfully reconstructed.

关键词： data hiding data protection data security image processing

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Parallelization and multi-threaded latency constrained parallel coding of JPEG xS 42

Parallelization and multi-threaded latency constrained paral...

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conference on applications of Digital image processing xLII

作者： Richter, Thomas Keinert, Joachim Foessel, Siegfried Fraunhofer IIS D-91058 Erlangen Germany

ISBN: (数字)9781510629684

ISBN: (纸本)9781510629684

This paper discusses the background, challenges, opportunities for parallelization of low-latency video transport of JPEG xS streams over the real-time network protocol (RTP). Transport of compressed video signals over a constant bitrate channel requires smoothing buffers at encoder and decoder side. To limit their sizes in partical implementations, part 2 of the JPEG xS standard defines a normative buffer model along a sequential hypothetical reference decoder. Due to its sequential nature, it cannot be directly applied to high-speed applications that necessarily depend on multithreading. In this paper, the JPEG xS Part 2 buffer model is introduced, then the current state of JPEG xS RTP transport standardization is discussed, and multiple strategies for multithreaded encoding under latency contraints within this application are reported and analyzed.

关键词： Computer programming wavelets Performance modeling image compression image quality image quality standards Video

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Quality Assessment for Natural and Screen Content images

Quality Assessment for Natural and Screen Content Images

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IEEE International conference on signal and image processing applications (IEEE ICSIPA)

作者： Loh, Woei-Tan Joseph, Annie Anak Bong, David B. L. Univ Malaysia Sarawak Fac Engn Kota Samarahan Malaysia

ISBN: (纸本)9781728133775

Quality assessment (QA) of screen content images (SCIs) has gained more and more popularity. SCIs are very different from natural images (NIs) which have been dealing with by most researchers in the literature. QA methods specifically designed for NIs also can be used to evaluate the quality of SCIs. Yet, their performances are unsatisfactory. This may due to the statistical differences of SCIs and NIs. In this paper, SCIs and NIs QA methods in the literature are being compared and studied for both SCIs and NIs benchmarked databases. It is found out that methods that incorporate gradient features work well for both SCIs and NIs. This points out a possible way to utilize gradient features to come out with a QA method that works for both SCIs and NIs simultaneously. Hence, application related to SCIs and NIs such as deep learning and multitasking for person tracking system can be improved with the QA method.

关键词： image quality screen content images natural images gradient

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Evaluation of Local Features for Near-Uniform Scene images

Evaluation of Local Features for Near-Uniform Scene Images

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IEEE International conference on signal and image processing applications (IEEE ICSIPA)

作者： Jong, Tze Kian Bong, David B. L. Univ Malaysia Sarawak Fac Engn Sarawak Malaysia

ISBN: (纸本)9781728133775

image stitching requires accurate matching of visual features to achieve good alignment. However, feature-based matching often has poor result particularly when image content is fairly near-uniform and thus it remains a challenging problem to be addressed. When the current state-of-the-art feature detectors unable to detect sufficient reliable corresponding keypoints, the output stitched images often suffer from misalignment, projective distortion and visible artefact. This paper presents a new experimental evaluation using especially near-uniform images for the performance of some well-known feature detectors, such as Harris, SIFT, SURF, BRISK and KAZE. In addition, we have also introduced RC/S-o score to compare spatial distribution of the correct matched keypoints in overlapping region between images. The results show that the best performed local feature detector is KAZE. However, none of the tested feature detectors can reach more than 50% spread of the overlapping region.

关键词： local features interest points image stitching near-uniform scenes quantitative evaluation

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Adaptive threshold vein enhancement method based on illuminance estimation

Adaptive threshold vein enhancement method based on illumina...

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IEEE Advanced Information Technology, Electronic and Automation Control conference (IAEAC)

作者： Hailan Kuang Fuying Guan xiaolin Ma xinhua Liu School of Information Engineering Wuhan University of Technology Wuhan China Key Laboratory of Fiber Optic Sensing Technology and Information Processing Wuhan University of Technology Ministry of Education Wuhan China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Infrared vein images often contain a lot of noise due to the performance defects of the infrared imaging system, and these images have the characteristics of low contrast, low signal-to-noise ratio, and blurred target details. In order to improve this situation, an adaptive threshold enhancement algorithm based on guided filter illuminance estimation (ATEBIE) is proposed to enhance the detailed information of the vein infrared image in this paper, especially the vein pattern, which is of great significance for applications such as vein display and vein recognition. Firstly, the infrared image of the vein is converted to the LAB color space representation to obtain the L-component of the image; Secondly, the multi-scale Gaussian blurring is performed on the component, and the noise is removed at the same time to obtain the initial illuminance estimation; then the guided filtering is used for accuracy illumination estimation; Finally, according to the illuminance image, an adaptive threshold is adopted to dynamically adjust the image to achieve the purpose of vein image enhancement. The experimental results show that the proposed algorithm not only suppresses the image noise very well, but also effectively enhances the vein texture details, and has a good application prospect.

关键词： image color analysis Veins Estimation Filtering algorithms Information filters image enhancement signal to noise ratio

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Human-computer Interactive System Development for Cloud Removal from Single images 7

Human-computer Interactive System Development for Cloud Remo...

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conference on Optical Metrology and Inspection for Industrial applications VII

作者： Wu, Feng Zhu, xifang xiang, Ruxi xu, Qingquan xu, Yang Sun, Qingcheng Changzhou Inst Technol Sch Elect & Informat Engn 666 Liaohe Rd Changzhou 213032 Jiangsu Peoples R China

ISBN: (数字)9781510639201

ISBN: (纸本)9781510639201

Remote sensing imaging is disturbed by clouds frequently and produces images with low contrast and poor resolution. Algorithms removing clouds from single remote sensing images are expected to improve their qualities and aroused worldwide interests. Compared with multi-image methods, cloud removal algorithms from single images reduce the demands for weather and improve the image collecting flexibility. In this paper, a human-computer interactive system for cloud removal from single images was developed according to the proposed cloud removal algorithm. Firstly, the distributions of clouds and sceneries in the contaminated remote sensing images were discussed. Features of the dual tree complex wavelet transform (DTCWT) to split image frequencies were investigated after the principle of DTCWT was analyzed. By combining the frequency features of DTCWT sub-bands and the frequency distributions of the remote sensing images, the cloud removal algorithm based on DTCWT was proposed, and its procedures were described completed. Then, a human-computer interactive system for cloud removal was developed in order to improve the cloud removal processing conveniences and achieve the best performance. The development schemes were introduced. The system structures were illustrated. The design methods of the camera driver and video signal output program were described. Communication streams between modules and human-computer interaction interfaces were designed further according to the cloud removal algorithm based on DTCWT. The system has a very good flexibility which permits the input of most parameters from users and is expect to achieve a best performance. Finally, the device of the system was completed and tested. image acquisition and cloud removal processing experiments were implemented by applying the human-computer interactive system. Cloud removal effects by adjusting parameters through the human-computer interaction interfaces were compared and evaluated. It proved that th

关键词： cloud removal dual tree complex wavelet transform human-computer interaction remote sensing image

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Analysis of deep learning architectures for turbulence mitigation in long-range imagery 2

Analysis of deep learning architectures for turbulence mitig...

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conference on Artificial Intelligence and Machine Learning in Defense applications II

作者： Vint, David Di Caterina, Gaetano Soraghan, John J. Lamb, Robert A. Humphreys, David Univ Strathclyde Ctr Signal & Image Proc Glasgow Lanark Scotland Leonardo MW Ltd Airborne & Space Syst Div Edinburgh Midlothian Scotland

ISBN: (纸本)9781510639003

In long range imagery, the atmosphere along the line of sight can result in unwanted visual effects. Random variations in the refractive index of the air causes light to shift and distort. When captured by a camera, this randomly induced variation results in blurred and spatially distorted images. The removal of such effects is greatly desired. Many traditional methods are able to reduce the effects of turbulence within images, however they require complex optimisation procedures or have large computational complexity. The use of deep learning for image processing has now become commonplace, with neural networks being able to outperform traditional methods in many fields. This paper presents an evaluation of various deep learning architectures on the task of turbulence mitigation. The core disadvantage of deep learning is the dependence on a large quantity of relevant data. For the task of turbulence mitigation, real life data is difficult to obtain, as a clean undistorted image is not always obtainable. Turbulent images were therefore generated with the use of a turbulence simulator. This was able to accurately represent atmospheric conditions and apply the resulting spatial distortions onto clean images. This paper provides a comparison between current state of the art image reconstruction convolutional neural networks. Each network is trained on simulated turbulence data. They are then assessed on a series of test images. It is shown that the networks are unable to provide high quality output images. However, they are shown to be able to reduce the effects of spatial warping within the test images. This paper provides critical analysis into the effectiveness of the application of deep learning. It is shown that deep learning has potential in this field, and can be used to make further improvements in the future.

关键词： Turbulence Mitigation Deep Learning CNN Turbulence Simulation

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A Dictionary-Based Generalization of Robust PCA with applications to Target Localization in Hyperspectral Imaging

A Dictionary-Based Generalization of Robust PCA with Applica...

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作者： Rambhatla, Sirisha Li, xingguo Ren, Jineng Haupt, Jarvis Department of Electrical and Computer Engineering University of Minnesota - Twin Cities MinneapolisMN55455 United States

We consider the decomposition of a data matrix assumed to be a superposition of a low-rank matrix and a component which is sparse in a known dictionary, using a convex demixing method. We consider two sparsity structures for the sparse factor of the dictionary sparse component, namely entry-wise and column-wise sparsity, and provide a unified analysis, encompassing both undercomplete and the overcomplete dictionary cases, to show that the constituent matrices can be successfully recovered under some relatively mild conditions on incoherence, sparsity, and rank. We leverage these results to localize targets of interest in a hyperspectral (HS) image based on their spectral signature(s) using the a priori known characteristic spectral responses of the target. We corroborate our theoretical results and analyze target localization performance of our approach via experimental evaluations and comparisons to related techniques. © 1991-2012 IEEE.

关键词： Hyperspectral imaging

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Quantitative Evaluation of 3D Reconstruction Using Filtered Back-Projection on xCAT Phantom 3

Quantitative Evaluation of 3D Reconstruction Using Filtered ...

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3rd International conference on Communications, signal processing, and their applications (ICCSPA)

作者： Farhat, Jumana Alatoom, Aseel Dhou, Salam Amer Univ Sharjah Biomed Engn Grad Program Sharjah U Arab Emirates Amer Univ Sharjah Dept Comp Sci & Engn Biomed Engn Grad Program Biosci & Bioengn Res Inst Sharjah U Arab Emirates

ISBN: (纸本)9781728120850

Filtered Back-Projection ( FBP) algorithm is the most common used reconstruction algorithm in Computed Tomography ( CT) systems. This paper presents the reconstruction of a 3D CT body phantom using FBP algorithm and MATLAB software. After obtaining the projections, different filters were tested: Ram-lak, shepp-logan, cosine, hamming and hann filters. In addition, a comparison was carried out for the quantitative image characteristics including the signal to noise ratio ( SNR), contrast to noise ratio ( CNR) and the spatial resolution for slices taken in three planes: axial, coronal and sagittal. Finally, the error was calculated for each reconstructed image. Initial results showed that shepp-logan and cosine filters generated most advantageous images in terms of image characteristics.

关键词： Filtered Back-Projection Computed Tomography image Reconstruction

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