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2010 International Symposium on Optomechatronic Technologies, ISOT 2010

作者： Lee, Hyunki Jeon, Jeong Yul Ko, Kwang Ill Cho, Hyungsuck Kim, Min Young R and D Robot Vision Team Kohyoung Co. Ltd. Seoul Korea Republic of Robotics Engineering Department DGIST Daegu Korea Republic of School of Electrical Engineering and Computer Science Kyungpook National University Daegu Korea Republic of

ISBN: (纸本)9781424476848

The ball grid array (BGA) has become one of the most popular packaging alternatives for high I/O devices in the industry with many advantages: high interconnection density and less packaging space and so on. In these days, the size of chip becomes small and the size of ball grid also becomes small, so the process of BGA alignment becomes more important and difficult. In this paper, the BGA alignment system before the oven process step is managed. The main difficult of inspecting the BGA alignment is that the substrate is always tilted due to irregular carrier size and in-line process. In this paper, to overcome this problem, tilt angle of substrate is measured by phase measuring profilometry (PMP), and then the compensated alignment offset calc ulation algorithm is suggested. The performance of our system is checked by a series of real experiments. © 2010 IEEE.

关键词： Ball grid arrays

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Robust color image segmentation through tensor voting

Robust color image segmentation through tensor voting

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International Conference on Pattern Recognition

作者： Moreno, Rodrigo Garcia, Miguel Angel Puig, Domenec Rovira I Virgili University Intelligent Robotics and Computer Vision Group Dept. of Computer Science and Mathematics Av. Països Catalans 26 43007 Tarragona Spain Autonomous University of Madrid Dept. of Informatics Engineering Francisco Tomas y Valiente 11 28049 Madrid Spain

ISBN: (纸本)9780769541099

This paper presents a new method for robust color image segmentation based on tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptation of tensor voting to both image denoising and robust edge detection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likely-inhomogeneous by means of the edginess maps generated in the first step. Third, the likely-homogeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmenter is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art. © 2010 IEEE.

关键词： Pixels

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MULTI-CAMERA POSITIONING FOR AUTOMATED TRACKING SYSTEMS IN DYNAMIC ENVIRONMENTS

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International Journal of Information Acquisition 2010年第3期7卷 225-242页

作者： YI YAO CHUNG-HAO CHEN BESMA ABIDI DAVID PAGE ANDREAS KOSCHAN MONGI ABIDI Visualization and Computer Vision Lab GE Global Research USA Department of Mathematics and Computer Science North Carolina Central University USA Imaging Robotics and Intelligent Systems Lab University of Tennessee Knoxville USA

Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, handoff safety margin is introduced to sensor planning so that sufficient overlapped FOVs among adjacent cameras are reserved for successful and smooth target transition. In this paper, we investigate the sensor planning problem when considering the dynamic interactions between moving targets and observing cameras. The probability of camera overload is explored to model the aforementioned interactions. The introduction of the probability of camera overload also considers the limitation that a given camera can simultaneously monitor or track a fixed number of targets and incorporates the target's dynamics into sensor planning. The resulting camera placement not only achieves the optimal balance between coverage and handoff success rate but also maintains the optimal balance in environments with various target densities. The proposed camera placement method is compared with a reference algorithm by Erdem and Sclaroff. Consistently improved handoff success rate is illustrated via experiments using typical office floor plans with various target densities.

关键词： Sensor planning visual surveillance multiple camera systems camera handoff

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Prostate Segmentation with Texture Enhanced Active Appearance Model

Prostate Segmentation with Texture Enhanced Active Appearanc...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Soumya Ghose Arnau Oliver Robert Martí Xavier Lladó Jordi Freixenet Joan C. Vilanova Fabrice Meriaudeau Laboratoire Le21 - UMR CNRS 5158 Université de Bourgogne Le Creusot France Computer Vision and Robotics Group Campus Montilivi Girona Spain Computer Vision and Robotics Group University of Girona Girona Spain Comput. Vision & Robot. Group Univ. of Girona Girona Spain Clinica Girona Girona Spain

Prostate contour segmented from Trans Rectal Ultra Sound (TRUS) and Magnetic Resonance (MR) images could improve inter-modality registration accuracy and reduce computational complexity of the procedure. However, prostate segmentation in each of these modalities is a challenging task in presence of imaging artifacts, intensity heterogeneities, and large inter patient shape variabilities of the prostate. We propose to use Haar wavelet approximation coefficients to extract texture features of the prostate region in both modalities to guide a deformable parametric model to segment the prostate in a multi-resolution framework. Principal Component Analysis (PCA) of the shape and texture information of the prostate region obtained from the training data aids contour propagation of the deformable parametric model. Prior knowledge of the optimization space is utilized for optimal segmentation of the prostate. Our method achieves a mean Dice Similarity Coefficient (DSC) value of 0.95±0.01, with mean segmentation time of 0.72±0.05 seconds in a leave-one-out validation framework with 25 TRUS images grabbed from a video sequence. DSC value of 0.88±0.06 with a mean segmentation time of 0.81±0.02 seconds was recorded for MR images when validated with 15 central slice images of 15 datasets from the MICCAI prostate segmentation challenge 2009. Our proposed method performs computationally efficient accurate multi-modal prostate segmentation in presence of intensity heterogeneities and imaging artifacts.

关键词： Image segmentation Active appearance model Shape Wavelet transforms Approximation methods Accuracy Principal component analysis

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Selective Submap Joining for underwater large scale 6-DOF SLAM

Selective Submap Joining for underwater large scale 6-DOF SL...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Josep Aulinas Xavier Lladó Joaquim Salvi Yvan R. Petillot Computer Vision and Robotics Group University of Girona Girona Spain Oceans Systems Lab Heriot Watt University Edinburgh United Kingdom

Autonomous Underwater Vehicles (AUVs) need positioning systems different than the Global Positioning System (GPS), which does not work in underwater scenarios. A possible solution to this lack of GPS signal are the Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms aim to build a map while simultaneously localize the vehicle within it. These algorithms suffer from several limitations in front of large scale scenarios. For instance, they do not perform consistent maps for large areas, mainly because uncertainties increase with the scenario. In addition, the computational cost increases with the map size. It has been demonstrated that the use of local maps reduces computational cost and improves map consistency. Following this idea, in this paper we propose a new SLAM technique based on using independent local maps, combined with a global level stochastic map. The global level contains the relative transformations between local maps. These local maps are updated once a new loop is detected and the amount of overlapping between local maps is high. Thus, maps sharing a high number of features are updated through fusion, maintaining the correlation between landmarks and vehicle. Experimental results on real data obtained from the REMUS-100 AUV show that our approach is able to obtain large map areas consistently.

关键词： Vehicles Simultaneous localization and mapping Sonar navigation Uncertainty Underwater vehicles

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Multimodal Prostate Registration Using Thin-Plate Splines from Automatic Correspondences

Multimodal Prostate Registration Using Thin-Plate Splines fr...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Jhimli Mitra Arnau Oliver Robert Martí Xavier Lladó Joan C. Vilanova Fabrice Meriaudeau Computer Vision and Robotics Group University of Girona Girona Spain Laboratoire Le2I - UMR CNRS 5158 Université de Bourgogne Le Creusot France Computer Vision and Robotics Group Campus Montilivi Girona Spain Clinica Girona Calle Joan Maragal126 Girona Spain

Registration is an important step during prostate biopsy with interventional Ultrasound (US) to project the Magnetic Resonance (MR) information of the corresponding slice of a pre-acquired MR volume of the same patient. This paper presents a method of deformable registration between US and MR prostate modalities using Thin-Plate Splines (TPS). The use of radial-basis functions such as splines is a typical approach for deformable registration wherein, TPS are more computationally efficient than Bsplines. However, registration with TPS employs strategic choice of correspondence points in the moving and reference images and therefore, has been rarely used by researchers for prostate registration. Aiming to deal with this issue, a novel method to automatically choose correspondence points (control points) based on the prostate geometry is presented in this paper. Shepard's interpolation is used with the TPS in order to deal with the interpolation artifacts produced by reverse TPS transform. To evaluate the accuracy of our correspondence generation method, two intuitive geometric methods for prostate contour sampling are also implemented. Our registration results are validated using 4 patient datasets obtaining an average DSC of 0.97 ± 0.01.

关键词： Interpolation Shape Spline Pixel Image resolution Biopsy Accuracy

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Submapping SLAM based on acoustic data from a 6-DOF AUV

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IFAC Proceedings Volumes 2010年第20期43卷 16-21页

作者： Josep Aulinas Chee Sing Lee Joaquim Salvi Yvan R. Petillot Computer Vision and Robotics group (ViCoRob) University of Girona 17071 Girona Spain Oceans Systems Lab School of EPS Heriot-Watt University EH144AS Edinburgh United Kindgom

Autonomous Underwater Vehicles (AUVs) need positioning systems besides the Global Positioning System (GPS), since GPS does not work in underwater scenarios. Possible solutions are the Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms aim to build a map while simultaneously localizing the vehicle within this map. However, they offer limited performance when faced with large scale scenarios. For instance, they do not create consistent maps for large areas, mainly because uncertainties increase with the scale of the scenario. In addition, the computational cost increases with the map size. The use of local maps reduces computational cost and improves map consistency. Following this idea, in this paper we propose a new SLAM approach that uses independent local maps together with a global level stochastic map. The global level contains the relative transformations between local maps. These local maps are updated once a new loop is detected. Local maps that are sharing a high number of features are updated through fusion, maintaining the correlation between landmarks and vehicle. Experimental results on real data obtained from the REMUS-100 AUV show that our approach is able to obtain large map areas consistently.

关键词： Autnonomous vehicles robotics navigation

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SLAM based Selective Submap Joining for the Victoria Park Dataset

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IFAC Proceedings Volumes 2010年第16期43卷 557-562页

作者： Josep Aulinas Xavier Lladó Joaquim Salvi Yvan R. Petillot Computer Vision and Robotics group (ViCoRob) University of Girona Girona 17071 Spain Ocean Systems Lab Heriot Watt University Edinburgh EH14 4AS United Kingdom

One of the main drawbacks of current SLAM algorithms is that they do not result in consistent maps of large areas, mainly because the uncertainties increase with the scenario. In addition, as the map size grows the computational costs increase, making SLAM solutions unsuitable for on-line applications. The use of local maps has been demonstrated to be useful in these situations, reducing computational cost and improving map consistency. Following this idea, this paper proposes a technique based on using independent local maps together with a global stochastic map. The global level contains the relative transformations between local maps, which are updated once a new loop is detected. In addition, the information within the local maps is also corrected. Thus, maps sharing a high number of features are updated through fusion and the correlation between landmarks and vehicle is maintained. Results on synthetic data and on the Victoria Park Dataset show that our approach is able to consistently map large areas and the computational costs are lower.

关键词： Localization mapping Extended Kalman Filter data association mobile robots

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Robust Color Image Segmentation through Tensor Voting

Robust Color Image Segmentation through Tensor Voting

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International Conference on Pattern Recognition

作者： Rodrigo Moreno Miguel Angel Garcia Domenec Puig Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Tarragona Spain Department of Informatics Engineering Autonomous University of Madrid Madrid Spain

ISBN: (纸本)9781424475421

This paper presents a new method for robust color image segmentation based on tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptation of tensor voting to both image denoising and robust edge detection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likely-inhomogeneous by means of the edginess maps generated in the first step. Third, the likely-homosgeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmenter is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art.

关键词： Pixel Image segmentation Tensile stress Robustness Image color analysis Image edge detection Noise measurement

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On Adapting Pixel-based Classification to Unsupervised Texture Segmentation

On Adapting Pixel-based Classification to Unsupervised Textu...

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International Conference on Pattern Recognition

作者： Jaime Melendez Domenec Puig Miguel Angel Garcia Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Tarragona Spain Department of Informatics Engineering Autonomous University of Madrid Madrid Spain

ISBN: (纸本)9781424475421

An inherent problem of unsupervised texture segmentation is the absence of previous knowledge regarding the texture patterns present in the images to be segmented. A new efficient methodology for unsupervised image segmentation based on texture is proposed. It takes advantage of a supervised pixel-based texture classifier trained with feature vectors associated with a set of texture patterns initially extracted through a clustering algorithm. Therefore, the final segmentation is achieved by classifying each image pixel into one of the patterns obtained after the previous clustering process. Multi-sized evaluation windows following a top-down approach are applied during pixel classification in order to improve accuracy. The proposed technique has been experimentally validated on MeasTex, VisTex and Brodatz compositions, as well as on complex ground and aerial outdoor images. Comparisons with state-of the-art unsupervised texture segmenters are also provided.

关键词： Image segmentation Pixel Clustering algorithms Accuracy Feature extraction Classification algorithms Image edge detection

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