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A fuzzy logic method on IC lead-frame surface inspection

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Jimin Li Weon-Geun Oh Chang-Joon Park Hyeon-Jin Kim Department of Computer Science Harbin Institute of Technology China Computer Vision Research Team Image Processing Department Computer & Software Technology Laboratory Electronics and Telecommunications Research Institute South Korea

ISBN: (纸本)0780354060

The inspection of lead-frame is important in semiconductor industry. During the production process, the quality control of lead-frame plays an important role. Here we introduce a method for inspection of contamination and plating quality of lead frame. The basic method of segmentation of interested lead surface into five classes is discussed based on the samples supplied from IC manufacturing company. A two-stage inspection method is introduced based on the basic five classes. The discussion of the system realization and experimental results show the idea.

关键词： Fuzzy logic Inspection Production Pattern recognition Photonic integrated circuits Shape image processing Laboratories computer science Lead compounds

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Elastic Shape Registration Using an Incremental Free Form Deformation Approach with the ICP Algorithm

Elastic Shape Registration Using an Incremental Free Form De...

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Canadian Conference on computer and Robot vision, CRV

作者： Hossam Abdelmunim Aly A. Farag Computer & Systems Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt Computer Vision and Image Processing Laboratory Electrical & Computer Engineering Department University of Louisville KY USA

Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems.

关键词： Shape Lattices Iterative closest point algorithm image resolution Mathematical model Equations Energy resolution

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A unified approach for detection, visualization, and identification of lung abnormalities in chest spiral CT scans

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International Congress Series 2003年第C期1256卷 998-1004页

作者： El-Baz, Ayman Farag, Aly A Falk, Robert La Rocca, Renato Computer Vision Image Processing Laboratory University of Louisville Louisville KY 40292 2301 South 3rd st. Lutz Hall RM 415 United States Medical Imaging Division Jewish Hospital United States Kentuckiana Cancer Institute Louisville KY 40202 Suite 502 100 East Liberty Street United States

This research aims at developing a fully automatic computer-Assisted Diagnosis (CAD) system for lung cancer screening using chest spiral CT scans. This paper presents two novel approaches for segmentation of the lung tissues from the surrounding structures in the chest cavity, and detection of the abnormalities in the lung tissues. The segmentation algorithm is hierarchical. The first step is to isolate the background from the chest cavity. The second step is to isolate the lungs from the surrounding structures (e.g., ribs, liver, and other organs that may appear in chest CT scans) by using Gibbs–Markov Random Field (GMRF). The third step is to isolate the abnormality (lung nodules), arteries, vines, bronchi, and bronchioles from the normal tissues. Finally, the abnormalities in the lungs are detected by using adaptive template matching;its parameters (mean, variance…) are estimated from the given data. In order to increase the speed of detecting lung nodules, we use genetic algorithms (GAs) to determine the target position in the observed image and to select an adequate template image from several reference patterns. © 2003, Elsevier Science B.V. All rights reserved.

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2D-3D registration of human ankle using X-ray and CT images

2D-3D registration of human ankle using X-ray and CT images

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Cairo International Biomedical Engineering Conference, CIBEC

作者： Ahmed Shalaby Aly A. Farag Adrianne Ross Todd Hockenbury Computer Vision and Image Processing Laboratory ECE Department University of Louisville Louisville KY USA Department of Orthopedic Surgery University of Louisville Louisville KY USA

In this paper, we introduce a new framework for registering pre-operative 3D volumetric data to intra-operative 2D images. We are particularly interested in examining the problem of aligning CT volumes to corresponding X-ray images. Our objective is to apply the 2D-3D registration in the field of orthopedics, specifically on ankle surgery. The long-term goal of this work is to apply this technique to ankle fusion surgery to determine the proper size and orientation of the screws which are used for fusing the bones together. In addition, we try to localize the best bone region to fix these screws. Our framework adopts the shear-warp factorization method to generate synthetic 2D images from the given 3D volume. Also, the alignment score is determined according to Exponential Correlation (EC) as a new similarity measure. We used a variety of methods to evaluate registration quality of our system. It has been tested on 15 clinical CT datasets. Evaluation results indicate the degree of accuracy of our registration framework.

关键词： Computed tomography X-ray imaging Surgery Fasteners Biomedical measurement Biomedical imaging Optimization

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Edgy salient local binary patterns in inter-plane relationship for image retrieval in Diabetic Retinopathy

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Procedia computer Science 2017年 115卷 440-447页

作者： Gajanan M. Galshetwar Laxman M. Waghmare Anil B. Gonde Subrahmanyam Murala Center of Excellence in Signal and Image Processing (COESIP) Department of ECE SGGSIET Nanded Maharashtra 431606 India Computer Vision and Pattern Recognition Laboratory Department of Electrical Engineering IIT Ropar Rupnagar 140001 India

In this paper, a novel approach for content based image retrieval (CBIR) in diabetic retinopathy (DR) is proposed. The concept of salient point selection and inter-plane relationship technique is used. Salient points are selected from edgy image and later using inter-planer relationship, Local Binary Patterns (LBPs) are calculated using the salient point as a center pixel. Our approach enhanced the results as we used color features in combination with LBP features. Experimentation is carried out on MESSIDOR database of 1200 retinal images, proposed approach has average precision of 57.82% as compared to the earlier approach whose average precision is 53.70%.

关键词： Content-Based image retrieval (CBIR) Diabetic Retinopathy (DR) Edgy Salient points Local Binary Patterns (LBPs)

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New Approach for Classification of Autistic vs. Typically Developing Brain Using White Matter Volumes

New Approach for Classification of Autistic vs. Typically De...

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Canadian Conference on computer and Robot vision, CRV

作者： Mostafa Abdelrahman Asem Ali Ahmed Farag Manuel F. Casanova Aly Farag Computer Vision & Image Processing Laboratory (CVIP) Univ. of Louisville Louisville KY Department of Psychiatry and Behavioral Sciences Univ. of Louisville Louisville KY

Autism is a complex developmental disability, characterized by deficits in social interaction, communication skills, range of interests, and occasionally the presence of stereotyped behaviors. Several studies show that changes in brain weight and volume over aging follow a unique trajectory in those affected by the condition~\cite{MICCAIMost00}. In this work, we develop a robust technique for evaluating the volume of white matter (WM), and use it as the main classification criteria. We perform MRI-based analysis on the brains of 14 autistic and 28 control subjects, male and female between aged 7 to 38 years. The proposed framework consists of several stages. First, the entire T1-weighted MRI scans are filtered out from noise using anisotropic diffusion filter. Then, the white matter (WM) is segmented from the skull. The segmentation framework is the search for maximum-a-posterior configurations in a Markov Gibbs Random Field (MGRF) model. A 3D mesh is then generated from the segmented WM. Finally, the volume of the 3D mesh is computed using a new algorithm. The experiments show accurate classification results of the proposed framework.

关键词： Autism image segmentation Solid modeling Magnetic resonance imaging Object segmentation Labeling Visualization

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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International Conference on Pattern Recognition

作者： Xie Jun H.T. Tsui Xia Deshen Image Processing and Computer Vision Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China Pattern Recognition Laboratory Department of Computer Science Nanjing University of Science and Technology China

ISBN: (纸本)076951695X

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties. The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. The performance in the experiments is better than those of two popular methods.

关键词： Object segmentation Maximum likelihood estimation image segmentation Layout Uncertainty image edge detection Shape measurement image processing Pattern recognition Gaussian distribution

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A Bayesian approach to error concealment in encoded video streams

A Bayesian approach to error concealment in encoded video st...

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IEEE International Conference on image processing

作者： P. Salama N. Shroff E.J. Delp Computer Vision and Image Processing Laboratory Purdue Multimedia Testbed Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA Purdue University System West Lafayette IN US

In ATM networks cell loss causes data to be dropped in the channel. When digital video is transmitted over these networks one must be able to reconstruct the missing data so that the impact of these errors is minimized. In this paper we describe a Bayesian approach to conceal these errors. Assuming that the digital video has been encoded using the MPEG1 or MPEG2 compression scheme, each frame is modeled as a Markov random field. A maximum a posteriori estimate of the missing macroblocks and motion vectors is described based on the model.

关键词： Bayesian methods Streaming media Intelligent networks Laboratories Markov random fields Video sequences Interpolation image reconstruction Motion estimation computer errors

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Intensity-difference based 3D video stabilization for planetary robots

Intensity-difference based 3D video stabilization for planet...

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International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Geovanni Martinez Image Processing and Computer Vision Research Laboratory (IPCV-IAB) Escuela de Ingeniería Eléctrica Universidad de Costa Rica San José Costa Rica

ISBN: (纸本)9781509035120

In this paper, an algorithm to remove the camera jitter from image sequences captured by planetary robots is investigated. First, the frame to frame surface 3D motion with respect to the camera coordinate system is estimated and integrated over time. The estimation is performed by maximizing a likelihood function of the frame to frame intensity differences measured at key observation points. Then, the jitter is determined as the perspective projection of the difference between the integrated surface 3D translation and a smoothed version of it. Finally, the stabilized video is synthesized by moving the entire content of each image with a displacement vector having the same magnitude but opposite direction to the estimated jitter for that image. The experimental results with synthetic data revealed real time operation with low latency and a reduction of the jitter in a factor of 20. Experimental results with real image sequences captured by a rover platform in indoor and outdoor conditions show very reliable and encouraging stabilization results.

关键词： Three-dimensional displays Cameras Robot vision systems Shape Robot kinematics Jitter

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Extending the Measurement Error Model of a Direct Visual Odometry Algorithm to Improve its Accuracy for Planetary Rover Navigation

Extending the Measurement Error Model of a Direct Visual Odo...

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Applied Science and Advanced Technology (iCASAT), 2019 IEEE International Conference on

作者： Geovanni Martinez Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingeniería Eléctrica Universidad de Costa Rica San José Costa Rica

ISBN: (数字)9781728131108

ISBN: (纸本)9781728131115

In this paper, the accuracy of a direct monocular visual odometry algorithm is improved. The algorithm is able to determine the position and orientation of a robot directly from intensity differences measured at observation points between consecutive images, captured by a monocular camera, rigidly attached to one side of its structure, tilted downwards. The improvement was achieved by extending the stochastic model of the intensity-difference measurement error, from considering only the camera noise, to one that also considers the intensity-difference measurement error due to the 3D shape error between the assumed and the true planetary surface shape. The corresponding covariance matrix was incorporated into a Maximum Likelihood estimator. According to the experimental results on irregular surfaces, where the 3D shape error is usually large, the accuracy of the visual odometry algorithm improved by a factor of 2 but with the cost of increasing the processing time also by the same factor.

关键词： Three-dimensional displays Cameras Measurement errors Visual odometry Robot vision systems Shape

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