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A Novel Level Set Method for Segmentation of Left and Right Ventricles from Cardiac MR images

A Novel Level Set Method for Segmentation of Left and Right ...

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

作者： Yu Liu Chunming Li Shuxu Guo Yihua Song Yue Zhao Center for Image Processing and Computer Vision Jilin University Center for Biomedical Image Computing and Analytics University of Pennsylvania Center for Key Laboratory of Medical Image Computing Ministry of Education Northeastern University

ISBN: (纸本)9781424479276

In this paper, we propose a novel level set method for segmentation of cardiac left and right ventricles based on the distance regularized level set evolution (DRLSE) framework [7] and the distance regularized two-layer level set (DR2LS) model [17]. First, DRLSE is applied to obtain a preliminary segmentation of left and right ventricles, which is then used to initialize the endocardial contour, which is represented by the zero level contour of the level set function in our method. Then, the epicardial contour is represented by a different level contour of the same level set function. These two level sets are optimized by an energy minimization process to best fit the true endocardium and epicardium. In order to ensure smoothly varying distance between the two level contours, we introduce a distance regularization constraint in the energy function. With the region-scalable fitting (RSF) energy [8] as the data term, our method is able to deal with intensity inhomogeneities in the images, which is a main source of difficulty in image segmentation. Our method has been tested on cardiac MR images with promising results.

关键词： Level set image segmentation Nonhomogeneous media Biomedical imaging Educational institutions Myocardium

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Offline learning of prototypical negatives for efficient online Exemplar SVM

Offline learning of prototypical negatives for efficient onl...

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IEEE Workshop on Applications of computer vision (WACV)

作者： Masato Takami Peter Bell Björn Ommer Robert Bosch GmbH Computer Vision Research Lab Hildesheim Germany Heidelberg Collaboratory for Image Processing & IWR University of Heidelberg Germany

Online searches in big image databases require sufficient results in feasible time. Digitization campaigns have simplified the access to a huge number of images in the field of art history, which can be analyzed by detecting duplicates and similar objects in the dataset. A high recall is essential for the evaluation and therefore the search method has to be robust against minor changes due to smearing or aging effects of the documents. At the same time the computational time has to be short to allow a practical use of the online search. By using an Exemplar SVM based classifier [12] a high recall can be achieved, but the mining of negatives and the multiple rounds of retraining for every search makes the method too time-consuming. An even bigger problem is that by allowing arbitrary query regions, it is not possible to provide a training set, which would be necessary to create a classifier. To solve this, we created a pool of general negatives offline in advance, which can be used by any arbitrary input in the online search step and requires only one short training round without the time-consuming mining. In a second step, this classifier is improved by using positive detections in an additional training round. This results in a classifier for the online search in unlabeled datasets, which provides high recall in short calculation time respectively.

关键词： Training Support vector machines Art Feature extraction Search problems Visualization image databases

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Text-independent writer identification by feature fusion

Text-independent writer identification by feature fusion

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International Conference on Intelligent Control and Information processing (ICICIP)

作者： Yongjie Hu Wenming Yang Youbin Chen Department of Electronic Engineering of Tsinghua University Zhejiang University Research interests include digital image processing and computer vision Department of Electronic Engineering of Tsinghua University Research interests include digital image processing and pattern recognition

ISBN: (纸本)9781479936519

This paper explores text-independent writer identification by combining Bag of Features (BoF), contour-hinge and SIFT scales feature. The BoF method adopted differs from the common BoF approach for writer identification in that it extracts SIFT descriptors and uses Locality-constrained Linear Coding to get feature vector of each document. The Locality-constrained Linear Coding (LLC) tries to reconstruct each feature through locality constraint and has much more discriminative power than the common used Vector Quantization (VQ). Contour-hinge feature can capture orientation and curvature of the ink trace. Modification is made to the original contour-hinge to improve the identification rate. Besides, we also use SIFT scale information and integrate these three kinds of features together. Experiments are conducted the challenging ICDAR2013 writer identification contest dataset and dataset for "ICFHR2012 Writer Identification Contest, Challenge 1: Latin Documents". The experiment results show that the proposed BoF approach outperforms the common ones that adopt VQ, and after the integration, our method achieves the best result on the entire ICDAR2013 and ICFHR2012 dataset under soft evaluation.

关键词： Feature extraction Vectors Encoding image reconstruction Text analysis Educational institutions

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Frameworks for multimodal biometric using sparse coding

Frameworks for multimodal biometric using sparse coding

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3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012

作者： Huang, Zengxi Liu, Yiguang Huang, Ronggang Yang, Menglong Vision and Image Processing Laboratory College of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9783642366680

In this paper, we will introduce three frameworks for multimodal biometric using sparse representation based classification (SRC), which has been successfully used in many classification tasks recently. The first framework is multimodal SRC at match score level (MSRC-s), in which feature of each modality is sparsely coded independently, and then their representation fidelities are used as match scores for multimodal classification. The other two frameworks are multimodal SRC at feature level (MSRC-f1, MSRC-f2), where features of all modalities are first fused and then classified by using SRC. The difference between them is that MSRC-f1 fuses the features to form a unique multimodal feature vector, while MSRC-f2 implicitly combines the features in an iterative joint sparse coding process. As a typical application, the fusion of face and ear for human identification is investigated by using the three frameworks. In our experiments, Principal Component Analysis (PCA) based feature extraction is applied. Many results demonstrate that the proposed multimodal methods are significantly better than the multimodal recognition using common classifiers. Among the SRC based methods, MSRC-s gets the top recognition accuracy in almost all the test items, which might benefit from allowing sparse coding independence for different modalities. © Springer-Verlag 2013.

关键词： Principal component analysis

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Extrinsic Calibration of a Fisheye Multi-Camera Setup Using Overlapping Fields of View

Extrinsic Calibration of a Fisheye Multi-Camera Setup Using ...

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IEEE Intelligent Vehicles Symposium

作者： Moritz Knorr Jose Esparza Wolfgang Niehsen Christoph Stiller Robert Bosch GmbH Corporate Research Computer Vision Research Lab Hildesheim Germany Heidelberg Collaboratory for Image Processing (HCI) Heidelberg University Heidelberg Germany Institute of Measurement and Control Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9781479936397

It is well known that the robustness of many computer vision algorithms can be improved by employing large field of view cameras, such as omnidirectional cameras. To avoid obstructions in the field of view, such cameras need to be mounted in an exposed position. Alternatively, a multi-camera setup can be used. However, this requires the extrinsic calibration to be known. In the present work, we propose a method to calibrate a fisheye multi-camera rig, mounted on a mobile platform. The method only relies on feature correspondences from pairwise overlapping fields of view of adjacent cameras. In contrast to existing approaches, motion estimation or specific motion patterns are not required. To compensate for the large extent of multi-camera setups and corresponding viewpoint variations, as well as geometrical distortions caused by fisheye lenses, captured images are mapped into virtual camera views such that corresponding image regions coincide. To this end, the scene geometry is approximated by the ground plane in close proximity and by infinitely far away objects elsewhere. As a result, low complexity feature detectors and matchers can be employed. The approach is evaluated using a setup of four rigidly coupled and synchronized wide angle fisheye cameras that were attached to four sides of a mobile platform. The cameras have pairwise overlapping fields of view and baselines between 2.25 and 3 meters.

关键词： setups corresponding baselines

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Contourlet transform based moving object segmentation

Contourlet transform based moving object segmentation

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2013 IEEE Conference on Information and Communication Technologies, ICT 2013

作者： Khare, Manish Nigam, Swati Srivastava, Rajneesh Kumar Khare, Ashish Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad Allahabad India

ISBN: (纸本)9781467357586

Moving object segmentation is an important step toward development of any computer vision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change detection method applied on Contourlet coefficients of two consecutive frames. We have chosen contourlet transform as it has high directionality and represents salient features of image such as edges, curves and contours in better way as compared with wavelet transform. The proposed method is simple and does not require any other parameter except contourlet coefficients. Results after applying the proposed method for segmentation of moving objects are compared with other state-of-the-art methods in terms of visual as well as quantitative performance measures viz. Average difference, Normalized absolute error and Pixel classification based measure. The proposed method is found to be better than other methods. © 2013 IEEE.

关键词： Contourlet transform

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Biorthogonal wavelet transform based image fusion using absolute maximum fusion rule

Biorthogonal wavelet transform based image fusion using abso...

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2013 IEEE Conference on Information and Communication Technologies, ICT 2013

作者： Prakash, Om Srivastava, Richa Khare, Ashish Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad Allahabad India Centre of Computer Education University of Allahabad Allahabad India

ISBN: (纸本)9781467357586

The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception. In recent past, different methods of image fusion have been proposed in literature both in spatial domain and wavelet domain. Spatial domain based methods produce spatial distortions in the fused image. Spatial domain distortion can be well handled by the use of wavelet transform based image fusion methods. In this paper, we propose a pixel-level image fusion scheme using multiresolution Biorthogonal wavelet transform (BWT). Wavelet coefficients at different decomposion levels are fused using absolute maximum fusion rule. Two important properties wavelet symmetry and linear phase of BWT have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus and multimodal images both free from any noise and in presence of additive white Gaussian noise and compared visually and quantitatively against existing spatial domain methods. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images. Fusion factor, entropy and standard deviation are used as quantitative quality measures of the fused image. © 2013 IEEE.

关键词： White noise

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When is a confidence measure good enough?

When is a confidence measure good enough?

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9th International Conference on computer vision Systems, ICVS 2013

作者： Márquez-Valle, Patricia Gil, Debora Hernàndez-Sabaté, Aura Kondermann, Daniel Computer Vision Center Universitat Autònoma de Barcelona Spain Heidelberg Collaboratory for Image Processing at the IWR University of Heidelberg Spain

ISBN: (纸本)9783642394010

Confidence estimation has recently become a hot topic in image processing and computer vision. Yet, several definitions exist of the term "confidence" which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions, thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. © 2013 Springer-Verlag.

关键词： Optical flows

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Recognition of hand punched Kannada Braille characters using knowledge based multi decision concept: Basic symbols

Recognition of hand punched Kannada Braille characters using...

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International Conference on Advances in Computing, ICAdC 2012

作者： Srinath, S. Ravi Kumar, C.N. Image Processing and Computer Vision Lab. Department of Computer Science and Engineering S.J. College of Engineering Mysore City Karnataka State 570 006 India

ISBN: (纸本)9788132207399

Technology has made the visually impaired life more comfortable. Access to textual information has become simple to the visually impaired community. Braille is widely used as communication tool for visually impaired people. The reading and writing communication for the visually impaired is available through the Braille language all over the world. Braille notations are available for most of the languages all over the world. Kannada is a south Indian language, which follows syllable writing method. People who work in association with visually impaired and can't understand Braille notation, require conversion of Braille document into a normal language representation. This paper presents an efficient algorithm for converting a Kannada Braille symbols into its equivalent normal version. Hand punched Kannada Braille document is used for the experimentation. The document image is segmented to extract Braille characters one at a time and compared with the knowledge base created to identify the equivalent normal version of it. Six different knowledge bases are created to reduce the search time complexity. © 2013 Springer.

关键词： Optical character recognition

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Model-based human teeth shape recovery from a single optical image with unknown illumination

Model-based human teeth shape recovery from a single optical...

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15th International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 2012

作者： Farag, Aly Elhabian, Shireen Abdelrehim, Aly Aboelmaaty, Wael Farman, Allan Tasman, David Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States School of Dentistry University of Louisville Louisville KY 40202 United States

ISBN: (纸本)9783642366192

Several existing 3D systems for dental applications rely on obtaining an intermediate solid model of the jaw (cast or teeth imprints) from which the 3D information can be captured. In this paper, we propose a model-based shape-from-shading (SFS) approach which allows for the construction of plausible human jaw models in vivo, without ionizing radiation, using fewer sample points in order to reduce the cost and intrusiveness of acquiring models of patients teeth/jaws over time. The inherent relation between the photometric information and the underlying 3D shape is formulated as a statistical model where the effect of illumination is modeled using Spherical Harmonics (SH) and the partial least square (PLS) approach is deployed to carry out the estimation of dense 3D shapes. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which can be automatically detected. Vis-à-vis dental applications, the results demonstrate a significant increase in accuracy in favor of the proposed approach. In particular, our approach is able to recover geometrical details of tooth occlusal surface as well as mouth floor and ceiling as compared to SFS-based approaches. © 2013 Springer-Verlag.

关键词： Ionizing radiation

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