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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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Novel surface registration using the grid closest point (GCP) transform

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IEEE International Conference on image processing

作者： S.M. Yamany M.N. Ahmed E.E. Hemayed A.A. Farag Computer Vision and Image Processing Laboratory Electrical Engineering Department University of Louisville Louisville KY USA

ISBN: (纸本)0818688211

A novel approach has been developed for fast registration of two sets of 3-D curves or surfaces. The technique is an extension of Besl and Mackay's (1992) iterative closest point (ICP) algorithm. This technique solves the computational complexity associated with the ICP algorithm by applying a novel grid closest point (GCP) transform and a genetic algorithm to minimize the cost function. A detailed description of the algorithm is presented along with a comparison of its performance versus several registration techniques. Two applications are presented in this paper. In the first, the algorithm is used to register 2-D head contours extracted from CT/MRI data to correct for possible mis-alignment caused by motion artifacts during scanning. In the second, the algorithm is used to register 3-D segments of the human jaw obtained using the shape from shading technique. Registration using the GCP/GA technique is found to be significantly faster and of comparable accuracy than two popular techniques in the computer vision and medical imaging literature.

关键词： Iterative algorithms Iterative closest point algorithm Computational complexity Genetic algorithms Cost function Head Data mining Computed tomography Magnetic resonance imaging Registers

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A system for human jaw modeling using intra-oral images

A system for human jaw modeling using intra-oral images

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： S.M. Yamany A.A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

A novel integrated system is developed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video camera. A modified Shape from Shading (SFS) technique using perspective projection and camera calibration is then used to extract accurate 3D information from a sequence of 2D images of the jaw. A novel technique for 3D data registration using Grid Closest Point (GCP) transform and genetic algorithms (GA) is used to register the output of the SFS stage. Triangulization is then performed, and a solid 3D model is obtained via a rapid prototype machine. The overall purpose of this research is to develop a model-based vision system for orthodontics that will replace traditional approaches and can be used in diagnosis, treatment planning, surgical simulation and implant purposes.

关键词： Humans Cameras computer vision Data acquisition Shape Calibration Data mining Genetic algorithms Solid modeling Prototypes

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Minimizing the topological structure of line images 7th

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7th Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition, SSPR 1998 and 2nd International Workshop on Statistical Techniques in Pattern Recognition, SPR 1998

作者： Kropatsch, Walter G. Burge, Mark Vienna University of Technology Institute of Automation 183/2 Pattern Recognition and Image Processing Group Treitlstr.3 WienA-1040 Austria Johannes Kepler University Institute of Systems Science Computer Vision Laboratory LinzA-4040 Austria

ISBN: (纸本)3540648585

We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) steps. A MLPP graph of a line image compliments the structural information in geometric graph representations like the run graph. Using such a graph and its dual, line image analysis systems can efficiently detect topological features like loops and holes and make use of relations like containment. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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Modified fuzzy c-mean in medical image segmentation

Modified fuzzy c-mean in medical image segmentation

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： N.A. Mohamed M.N. Ahmed A. Farag Computer Vision and Image Processing Laboratory E.E. Department University of Louisville Louisville KY USA

This paper describes the application of fuzzy set theory in medical imaging, namely the segmentation of brain images. We propose a fully automatic technique to obtain image clusters. A modified fuzzy c-mean (FCM) classification algorithm is used to provide a fuzzy partition. Our new method, inspired from the Markov Random Field (MRF), is less sensitive to noise as it filters the image while clustering it, and the filter parameters are enhanced in each iteration by the clustering process. We applied the new method on a noisy CT scan and on a single channel MRI scan. We recommend using a methodology of over segmentation to the textured MRI scan and a user guided-interface to obtain the final clusters. One of the applications of this technique is TBI recovery prediction in which it is important to consider the partial volume. It is shown that the system stabilizes after a number of iterations with the membership value of the region contours reflecting the partial volume value. The final stage of the process is devoted to decision making or the defuzzification process.

关键词： Biomedical imaging image segmentation Filters Magnetic resonance imaging Fuzzy set theory Brain Classification algorithms Clustering algorithms Partitioning algorithms Markov random fields

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CVIPtools: A software package for computer imaging education

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computer Applications in Engineering Education 1998年第3期5卷

作者： Mark Zuke Scott E. Umbaugh Computer Vision and Image Processing Laboratory Southern Illinois University at Edwardsville Edwardsville IL 62026

New computer imaging software is described. CVIPtools illustrates principles of computer imaging and enables rapid development of complex algorithms. The easy-to-use graphical user interface makes available over 170 functions to students and artists, astronomers, geographers, and others who want to explore imaging but lack programming knowledge. © 1997 John Wiley & Sons, Inc. Comput Appl Eng Educ 5: 213–220, 1997

关键词： computer imaging computer vision image processing image-processing software

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Feature extraction in image analysis

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 1997年第4期16卷 62-73页

作者： Umbaugh, SE Wei, YS Zuke, M Computer Vision and Image Processing Laboratory Southem Illinois University Edwardsville USA

images are important for many biomedical applications. Here, the authors focus on the feature-extraction part of the image analysis process. The following topics are dealt with: feature vectors and feature spaces; binary object features; histogram features; color features; spectral features; feature extraction using CVIPtools; analysis/preprocessing.

关键词： Feature extraction image analysis Robustness image color analysis Pixel Filtering Colored noise Frequency Data mining Information analysis

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1.5V resistive fuse for image smoothing and segmentation

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ELECTRONICS LETTERS 1997年第10期33卷 851-852页

作者： Athreya, JKV Gregson, PH Department of Electrical Engineering Computer Vision and Image Processing Laboratory Technical University of Nova Scotia Halifax Canada

A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage;it switches off if the differential voltage is higher than the set value. The useful operation range of the circuit is 0.4V with a supply voltage of 1.5V and threshold voltages of V-Tn = 0.828V and V-Tp = -0.56V for n and g channel MOSFETs, respectively.

关键词： image processing segmentation (image processing)

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Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

引用

1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Ahmed, MN Farag, AA Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)0780341236

In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be apdated to real-time imaging scenarios.

关键词： segmentation pattern analysis learning in vision

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3D reconstruction of the human jaw from a sequence of images

3D reconstruction of the human jaw from a sequence of images

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Conference on computer vision and Pattern Recognition (CVPR)

作者： M. Ahmed S. Yamany E. Hemayed S. Ahmed S. Roberts A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

关键词： image reconstruction Humans computer vision Data acquisition Cameras Shape Data mining Genetic algorithms Implants Machine vision

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