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Automatic Field of View Extraction with Variable Enhancement of Color Fundus images 14

Automatic Field of View Extraction with Variable Enhancement...

引用

14th IEEE India Council International Conference, INDICON 2017

作者： Kulkarni, Sushma Kamble, Ravi Kokare, Manesh Dept. of Electronics and Telecom. Engg. Center of Excellence in Signal and Image Processing SGGS Institute of Engineering and Technolgy Nanded431606 India

ISBN: (纸本)9781538643181

Most retinal images suffers from large size with inadequate contrast and brightness. Automated field of view (FOV) extraction and image enhancement significantly increases the performance of image analysis for diabetic retinopathy (DR) detection. This paper presents a simple and automated FOV extraction technique using only one horizontal and vertical scan lines. The FOV image further enhanced using the guided filter with variable enhancement factor. The proposed method has been applied on five publicly available databases. The accuracy of FOV extraction is obtained 100% for Diaretdb0 and ONHSD databases, 99.91% for messidor, 99.32% for E-optha and 98.87% for Diaretdb1 database. The experimental results shows that, proposed method gives the good enhancement on five different databases compared with the existing state-of-the-art methods. Overall, the proposed method can be used as a effective preprocessing tool for accurate detection of lesions in retinal image analysis. © 2017 IEEE.

关键词： Database systems

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Shadow detection on 3d point cloud

Shadow detection on 3d point cloud

引用

3D image processing, Measurement (3DIPM), and Applications 2016

作者： Sheng, Shuyang Jenkins, B. Keith Signal and Image Processing Institute Ming Hsieh Dept. of Electrical Engineering University of Southern California Los AngelesCA United States

Shadow detection is undergoing active research because it plays an important role in scene understanding, and has a wide range of applications including household robots and autonomous cars. In this effort, we present a novel approach to detect cast shadows on 3D point clouds. Point Cloud Library (PCL) is used to perform plane detection on point clouds. A Markov Random Field (MRF) is then constructed on the detected plane region, with an energy term that combines plane labels, dept. cues and brightness cues. The resulting system is tested against USC Shadow, a dataset we collected in a controlled environment, as well as selected scenes from NYU dept., a dataset that contains 1449 RGB-D images of various indoor scenes. Our system shows very stable performance even on complicated scenes and heavily textured planes. © 2016 Society for Imaging Science and Technology.

关键词： Markov processes

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Performance analysis of co-located and distributed MIMO radar for micro-Doppler classification 13

Performance analysis of co-located and distributed MIMO rada...

引用

13th European Radar Conference, EuRAD 2016

作者： Özcan, Mustafa Buǧra Gürbüz, Sevgi Zübeyde Persico, Adriano Rosario Clemente, Carmine Soraghan, John Dept. of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Turkey Centre for Excellence in Signal and Image Processing University of Strathclyde Glasgow United Kingdom

ISBN: (纸本)9782874870453

Over the past few years, the use of Multiple Input Multiple Output (MIMO) radar has gained increased attention as a way to mitigate the degredation of micro-Doppler classification performance incurred when the aspect angle approaches 90 degrees. In this work, the efficacy of co-located MIMO radar is compared with that of distributed MIMO. The performance anaylsis is accomplished for three different classification problems: 1) discrimination of a walking group of people from a running group of people;2) identification of individual human activities, and 3) classification of different types of walking. In the co-located configuration each radar is placed side by side so as to form a line. In the distributed configuration, the radar positions are separated to observe the subjects from different angles. Starting from the cadence velocity diagram (CVD), the Pseudo-Zernike moments based features are extracted because of their robustness with respect to unwanted scalar and angular dependencies. Two different approaches to integrate the features obtained from multi-aspect data are compared: concatenation and principal component analysis (PCA). Results show that a distributed MIMO configuration and use of PCA to fuse multi-perspective features yields higher classification performance as compared to a co-located configuration or feature vector concatenation. © 2016 EuMA.

关键词： Principal component analysis

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AUTOMATIC SEGMENTATION OF FETAL BRAIN USING DIFFUSION-WEIGHTED IMAGING CUES

AUTOMATIC SEGMENTATION OF FETAL BRAIN USING DIFFUSION-WEIGHT...

引用

International Symposium on Biomedical Imaging

作者： Rosita Shishegar Anand A. Joshi Mary Tolcos David W. Walker Leigh A. Johnston Dept. Electrical & Electronic Engineering University of Melbourne Australia Signal and Image Processing Institute Department of Electrical Engineering Systems University of Southern California Los Angeles USA School of Health and Biomedical Sciences RMIT University Bundoora Australia Monash Institute of Medical Research The Ritchie Centre Monash University Australia

ISBN: (纸本)9781509011735

Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.

关键词： Segmentation atlas-free fetal brain diffusion-weighted imaging tractography

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Anomaly detection techniques in surveillance videos

Anomaly detection techniques in surveillance videos

引用

International Congress on image and Signal processing, BioMedical engineering and Informatics (CISP-BMEI)

作者： Xiaoli Li Ze-min Cai Dept. of Electronic Engineering Shantou University Shantou China Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou China

ISBN: (纸本)9781509037117

In recent years, a dramatically increasing number of surveillance cameras have been installed to monitor private and public spaces and areas. Video surveillance is seen as an effective way to ensure our security. Therefore, modeling activity patterns and human behaviors for detection or recognition of peculiar event is a critical technology which has attracted remarkable research interest in the last few years. Various methods have been developed to build intelligent vision systems, this article extensively explain the current improvement made toward video-based human abnormal activity detection and wide applications in various fields range from monitoring in public spaces to personal health rehabilitation.

关键词： Videos Surveillance Optical imaging Feature extraction Support vector machines Adaptive optics Neural networks

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Performance analysis of co-located and distributed MIMO radar for micro-Doppler classification

Performance analysis of co-located and distributed MIMO rada...

引用

European Radar Conference (EURAD)

作者： Mustafa Buğra Özcan Sevgi Zübeyde Gürbüz Adriano Rosario Persico Carmine Clemente John Soraghan Dept. of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Turkey Centre for Excellence in Signal and Image Processing University of Strathclyde Glasgow United Kingdom

Over the past few years, the use of Multiple Input Multiple Output (MIMO) radar has gained increased attention as a way to mitigate the degredation of micro-Doppler classification performance incurred when the aspect angle approaches 90 degrees. In this work, the efficacy of co-located MIMO radar is compared with that of distributed MIMO. The performance anaylsis is accomplished for three different classification problems: 1) discrimination of a walking group of people from a running group of people; 2) identification of individual human activities, and 3) classification of different types of walking. In the co-located configuration each radar is placed side by side so as to form a line. In the distributed configuration, the radar positions are separated to observe the subjects from different angles. Starting from the cadence velocity diagram (CVD), the Pseudo-Zernike moments based features are extracted because of their robustness with respect to unwanted scalar and angular dependencies. Two different approaches to integrate the features obtained from multi-aspect data are compared: concatenation and principal component analysis (PCA). Results show that a distributed MIMO configuration and use of PCA to fuse multi-perspective features yields higher classification performance as compared to a co-located configuration or feature vector concatenation.

关键词： MIMO Feature extraction Principal component analysis Radar Legged locomotion Robustness Distributed databases

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Notice of Removal: Alignment of optic nerve head optical coherence tomography B-scans in right and left eyes

Notice of Removal: Alignment of optic nerve head optical coh...

引用

IEEE International Conference on image processing

作者： Marzieh Mokhtari Hossein Rabbani Alireza Mehri-Dehnavi Biomedical Engineering Dept. Isfahan University of Medical Sciences Isfahan Iran Medical Image & Signal Processing Research Center Isfahan Univ. of Medical Sciences Isfahan Iran

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KardiaTool: An Integrated POC Solution for Non-invasive Diagnosis and Therapy Monitoring of Heart Failure Patients

KardiaTool: An Integrated POC Solution for Non-invasive Diag...

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

作者： Evanthia E. Tripoliti Georgia S. Karanasiou Pinelopi Ioannidou Petros Toumpaniaris Yorgos Goletsis Joan Baussels Tommaso Lomonaco Norman Pfeiffer Raphal Anasthase Aliki Tsopela Boris Leekens Katerina K. Naka Jean-Christophe Lourme Pietro Salvo Trifon Liakopoulos Jake Jordan Joseph Gallagher Abdelhamid Errachid Dimitrios I. Fotiadis Institute of Molecular Biology and Biotechnology Heraklion GR Universita degli Studi di Pisa Pisa Toscana IT Department of Economics University of Ioannina GR Ioannina Greece The Instituto de Microelectrónica de Barcelona IMBCNM (CSIC) Bellaterra Campus UAB Spain The Department of Chemistry and Indurstrial Chemistry University of Pisa Italy Image Processing and Medical Engineering Department Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Panepistimio Ioanninon Ioannina GR Micronit Microtechnologies B.V. PV Enschede The Netherlands Interuniversitair Microelectronica Centrum (IMEC) Leuven Kapeldreef Belgium Department of Cardiology University of Ioannina GR Ioannina Greece University of Surrey Guildford Surrey GB National University of Ireland Dublin IE Universite de Lyon Lyon Auvergne-RhÃ´ne-Alpes FR Idryma Technologias kai Ereunas Heraklion GR gHealth Research Group National University Of Ireland Belfield University College Dublin Dublin Ireland Université de Lyon Institut de Sciences Analytiques (ISA) –UMR 5280 Villeurbanne France Department of Biomedical Research and the Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems Institute of Molecular Biology and Biotechnology University of Ioannina Ioannina GR FORTH Ioannina Greece

The aim of this work is to present KardiaTool platform, an integrated Point of Care (POC) solution for noninvasive diagnosis and therapy monitoring of Heart Failure (HF) patients. The KardiaTool platform consists of two components, KardiaPOC and KardiaSoft. KardiaPOC is an easy to use portable device with a disposable Lab-on-Chip (LOC) for the rapid, accurate, non-invasive and simultaneous quantitative assessment of four HF related biomarkers, from saliva samples. KardiaSoft is a decision support software based on predictive modeling techniques that analyzes the POC data and other patient's data, and delivers information related to HF diagnosis and therapy monitoring. It is expected that identifying a source comparable to blood, for biomarker information extraction, such as saliva, that is cost-effective, less invasive, more convenient and acceptable for both patients and healthcare professionals would be beneficial for the healthcare community. In this work the architecture and the functionalities of the KardiaTool platform are presented.

关键词： Biomarkers Hafnium Electronic mail Monitoring Medical treatment Microfluidics

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HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM FIELDS WITH STOCHASTIC CLIQUES

HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM...

引用

IEEE International Conference on image processing

作者： F. Y. Li M. J. Shafiee A. G. Chung B. Chwyl F. Kazemzadeh A. Wong J. Zelek Vision & Image Processing Lab Systems Design Engineering Dept. University of Waterloo

ISBN: (纸本)9781479983407

The reconstruction of high dynamic range (HDR) images via conventional camera systems and low dynamic range (LDR) images is a growing field of research in image acquisition. The radiance map associated with the HDR image of a scene is typically computed using multiple images of the same scene captured at different exposures (i.e., bracketed LDR imzages). This approach, though inexpensive, is sensitive to noise under high camera ISO. Each bracketed image is associated with a different level of noise due to the change in exposure time, and the noise is further amplified when tone-mapping the HDR image for display. A new framework is proposed to address the associated noise in the context of random fields. The estimation of the HDR image from a set of LDR images is formulated as a stochastically fully connected conditional random field where the spatial information is incorporated to compute the HDR value in combination with the LDR image values. Experimental results show that the proposed framework compensated the non-stationary ISO noise while preserving the boundaries in the estimated HDR images.

关键词： High Dynamic Range Imaging Conditional Random Fields image Denoising HDR Reconstruction SFCRF image denoising hot dry rocks GATA3 gene LAND DISPOSAL RESTRICTIONS Noise images HIGH DYNAMIC RANGE Markov random fields field surveys Noise levels Brackets Cameras

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TIGER: A TEXTURE-ILLUMINATION GUIDED ENERGY RESPONSE MODEL FOR ILLUMINATION ROBUST LOCAL SALIENCY

TIGER: A TEXTURE-ILLUMINATION GUIDED ENERGY RESPONSE MODEL F...

引用

IEEE International Conference on image processing

作者： B. Chwyl A. G. Chung F. Y. Li A. Wong D. A. Clausi Vision & Image Processing Lab Systems Design Engineering Dept. University of Waterloo

ISBN: (纸本)9781479983407

Local saliency models are a cornerstone in image processing and computer vision, used in a wide variety of applications ranging from keypoint detection and feature extraction, to image matching and image representation. However, current models exhibit difficulties in achieving consistent results under varying, non-ideal illumination conditions. In this paper, a novel texture-illumination guided energy response (TIGER) model for illumination robust local saliency is proposed. In the TIGER model, local saliency is quantified by a modified Hessian energy response guided by a weighted aggregate of texture and illumination aspects from the image. A stochastic Bayesian disassociation approach via Monte Carlo sampling is employed to decompose the image into its texture and illumination aspects for the saliency computation. Experimental results demonstrate that higher correlation between local saliency maps constructed from the same scene under different illumination conditions can be achieved using the TIGER model when compared to common local saliency approach, i.e., Laplacian of Gaussian, Difference of Gaussians, and Hessian saliency models.

关键词： Local saliency model Illumination robust Local features Bayesian estimation Stochastic Texture Illumination illumination Lighting Stochastic Bayes methods textures local image feature texture images Gauss Energy responses image representation image matching

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