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检索条件"机构=Computer Vision and Image Analysis Laboratory Department of Electrical and Computer Engineering"

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image and video descriptors

Image and video descriptors

引用

Workshops on image Processing Theory, Tools and Applications, IPTA

作者： Abdenour Hadid Machine Vision Group Computer Science and Engineering Laboratory Department of Electrical and Information Engineering University of Oulu Finland

Feature (or descriptor) extraction from images and videos is a very crucial task in almost all computer vision systems. It consists of extracting characteristics describing important information in the images and videos. Different global (or holistic) methods such as Principal Component analysis (PCA) have been widely studied and applied but lately local descriptors (such as LBP, SIFT and Gabor) have gained more attention due to their robustness to challenges such as pose and illumination changes. This tutorial gives an exhaustive overview of different image and video descriptors which can be found in literature with an emphasis on the most recent developments in the field. The tutorial will then focus on one or two state-of-the-art descriptors to demonstrate step by step how to successfully apply them to various computer vision problems such as biometrics, texture analysis, image and video retrieval, motion and activity analysis, human-computer interaction etc.

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Automatic mask creation and feature analysis for detectionof IVDD in canines

Automatic mask creation and feature analysis for detectionof...

引用

International Conference on computer Sciences and Convergence Information Technology (ICCIT)

作者： Jakia Afruz Jesse Phelps Scott E Umbaugh Dominic J. Marino Catherine A. Loughin Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Southern Illionis University Edwardsville Edwardsville IL USA Long Island Veterinary Specialists Plainview NY USA

Intervertebral disc disease (IVDD) is a condition that affects both humans and canines. This disease is painful and degrades the quality of life for those that suffer from it. The current diagnostic methods for this disease are Magnetic Resonance Imaging (MRI) and/or Computed Axial Tomography (CAT scan). Both of these diagnostic methods are expensive and time consuming and involve patients being exposed to radiation and strong magnetic fields. In canines in particular, the amount of time it takes to perform one of these scans makes it necessary to sedate the animal as the patient needs to be still during the diagnostic procedure. Use of thermographic imaging for diagnosis, or at least prescreening, patients for IVDD will save money, time and possibly prevent needless radiation exposure. This paper attempts to show that thermal imaging of patients that are candidates for IVDD may be used diagnostically or as a prescreening method.

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Retinal vessel segmentation using color image morphology and local binary patterns

Retinal vessel segmentation using color image morphology and...

引用

Iranian Machine vision and image Processing (MVIP)

作者： Seyed Mohsen Zabihi Morteza Delgir Hamid Reza Pourreza Machine Vision Laboratory Eye Images Analysis Research Group Computer Engineering Department Ferdowsi University of Mashhad Iran

In this paper, an automated retinal vessel extraction algorithm is represented. A multi-scale morphological algorithm is used for local contrast enhancement of color retinal image. This method enhances vessels not only in color image, but also in the three color components of that image. After feature extraction using LBP and spatial image processing, MLP as a classifier segments the pixels into vessels and non-vessels. Finally, in post processing step, we used binary morphologies for noise removing and smoothing. The performance of the proposed algorithm is tested on the images of DRIVE database.

关键词： Pixel Retina Feature extraction image segmentation image color analysis Biomedical imaging Blood vessels

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Frame Interpolation Method Based on Adaptive Threshold and Adjacent Pixels

Frame Interpolation Method Based on Adaptive Threshold and A...

引用

International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Hyeongchul Oh Joohyun Lee Changki Min Jechang Jeong Image Communication and Signal Processing Laboratory Department of Electrical and Computer Engineering Hanyang University Seoul South Korea

This paper presents a frame interpolation algorithm using the motion information of some object within the estimated blocks. The proposed algorithm uses two initial frames that are generated based on the backward and forward frames using the motion vectors. In this process, the occlusion regions are occurred in two initial frames since the optimal block is only selected by threshold. Furthermore, the regions are irregularly appeared because of that the selected block is interpolated on half position between the estimated motion vectors. Two initial frames are merged to interpolate the occlusion regions. Also, the occlusion areas, which are still existence in the merged frame, are interpolated by using the neighboring pixel information and the available data in the occlusion block. In this paper, the experimental results show that the performance of the proposed algorithm has better PSNR and the visual quality than the conventional algorithms.

关键词： Pixel PSNR Interpolation Visualization Motion compensation Algorithm design and analysis Motion estimation

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Motion Compensated Frame Interpolation Using Adaptive Adjacency Pixel Information

Motion Compensated Frame Interpolation Using Adaptive Adjace...

引用

International Conference on computer Graphics, Imaging and Visualization, CGIV

We propose an adaptive motion compensated frame interpolation scheme which is capable of developing a frame rate from a lower number into a higher number and a decoded video quality at the decoder. The proposed algorithm utilizes the preliminary frames of the forward and backward directions using bilateral prediction. In the processing of the preliminary frames, an additional interpolation is performed to fill the occlusion areas. If the calculated values between the reference and current frames are larger than the predetermined threshold, the block is chosen as the occlusion area. In addition, we performed a re-search in order to acquire the best blocks, taking into account the number of available adjacent blocks for the occlusion areas. The experimental results show that the performance of the proposed algorithm has better PSNR and visual quality than those of the conventional methods.

关键词： Interpolation Pixel Robustness PSNR Motion estimation Algorithm design and analysis Motion compensation

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Deep Spatiotemporal Feature Learning with Application to image Classification

Deep Spatiotemporal Feature Learning with Application to Ima...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Thomas P. Karnowski Itamar Arel Derek Rose Image Science and Machine Vision Group Oak Ridge National Laboratory Oak Ridge TN USA Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

Deep machine learning is an emerging framework for dealing with complex high-dimensionality data in a hierarchical fashion which draws some inspiration from biological sources. Despite the notable progress made in the field, there remains a need for an architecture that can represent temporal information with the same ease that spatial information is discovered. In this work, we present new results using a recently introduced deep learning architecture called Deep Spatio-Temporal Inference Network (DeSTIN). DeSTIN is a discriminative deep learning architecture that combines concepts from unsupervised learning for dynamic pattern representation together with Bayesian inference. In DeSTIN the spatiotemporal dependencies that exist within the observations are modeled inherently in an unguided manner. Each node models the inputs by means of clustering and simple dynamics modeling while it constructs a belief state over the distribution of sequences using Bayesian inference. We demonstrate that information from the different layers of this hierarchical system can be extracted and utilized for the purpose of pattern classification. Earlier simulation results indicated that the framework is highly promising, consequently in this work we expand DeSTIN to a popular problem, the MNIST data set of handwritten digits. The system as a preprocessor to a neural network achieves a recognition accuracy of 97.98% on this data set. We further show related experimental results pertaining to automatic cluster adaptation and termination.

关键词： computer architecture Training Artificial neural networks Measurement Pixel Machine learning Feature extraction

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Building detection in satellite images by textural features and Adaboost

Building detection in satellite images by textural features ...

引用

IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)

作者： Melih Cetin Ugur Halici Örsan Aytekin Computer Vision and Intelligent Systems Research Laboratory Department of Electrical and Electronics Engineering Middle East Technical University Turkey

A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike moments, Circular-Mellin features, Haralick features, Fourier Power Spectrum, Wavelets, Gabor Filters, and a set features extracted from HSV color space are extracted. Adaboost learning algorithm is employed for both classification and determining the beneficial feature subset, due to its feature selector nature. Some operation including morphological operators are applied for post processing. The approach was tested on a set of satellite images having different types of buildings and promising experimental results are achieved.

关键词： Buildings Feature extraction Pixel Satellites Classification algorithms Remote sensing image color analysis

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Techniques for automatic magnetic resonance image classification

Techniques for automatic magnetic resonance image classifica...

引用

International Conference on Genetic and Evolutionary Computing

作者： Chen, Hsian-Min Chen, Shih-Yu Chai, Jyh Wen Chen, Clayton Chi-Chang Wu, Chao-Cheng Ouyang, Yen-Chieh Tsai, Ching Tsorng Yang, Ching-Wen Lee, San-Kan Chang, Chein-I Department of Biomedical Engineering Hungkuang University Taichung Taiwan Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Section of Radiology College of Medicine China Medical University Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Computer Science Department Tunghai University Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769542812

Designing and developing automatic techniques for magnetic resonance images (MR) for data analysis is very challenging. One popular and public available method, FAST (FMRIB Automatic Segmentation Tool) has been widely used for automatic brain tissue segmentation for this purpose. This paper investigates limitations of this software algorithm on implementation and further develops a new approach to automatic MR brain tissue classification. The proposed new technique first implements an unsupervised training sample generation process (UTSGP) which includes a Pixel Purity Index (PPI) to generate an initial set of training samples that are further refined by a Support Vector Machine. The resulting training samples are then as a set of training samples for an Iterative Fisher's Linear Discriminant analysis (IFLDA) which implements FLDA iteratively to improve classification. In order to conduct a fair comparison synthetic images are used for performance evaluation. Experimental results show that our proposed technique is superior in practical implementation to this software algorithm in several aspects of generalization ability, flexibility of choosing number of classes to be classified, avoidance of inconsistent results caused by different initial conditions. © 2010 IEEE.

关键词： Support vector machines

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Implementation and analysis of integration GSM/GPRS modem in a TMS320VC6713 digital signal processor for vehicle location

Implementation and analysis of integration GSM/GPRS modem in...

引用

International Conference on computer and Communication engineering, ICCCE

作者： H. A. Rahim R. B. Ahmad A. S. M. Zain U. U. Sheikh School of Computer and Communication Engineering Universiti Malaysia Pedis Kangar Perlis Malaysia Computer Vision Video and Image Processing Research Laboratory (CVVIP) Department of Microelectronics and Computer Engineering Universiti Teknologi Malaysia Johor Bahru Johor Malaysia

The rapidly evolving wireless communications environment and 3G, where the standard are constantly created and modified, has given rise to the integration of GPS (Global Positioning System) and GSM (Global System for Mobile Communication). This integration has been widely applied in many disciplines including Intelligent Transportation System (ITS) and Logistic Management to aid the users to locate their vehicles remotely. Further on, the fast growth of city transportation also has stimulated the development of VMS where it is recognized as one of the major components of ITS. However, this system is rarely being implemented on embedded system using DSP processor. Thus, this paper discusses design and implementation of GSM/GPRS integration in a TMS320VC6713 for Vehicle Location that permits users to communicate with their vehicles via a Short Message Service (SMS). This system provides an alternative solution to solve vehicle theft and hijacking problems where the system is able track the real-time moving car location by using cellular phone. The system performance analysis has been carried out where the executions of three functions have been measured in clock cycles.

关键词： GSM Digital signal processing Global Positioning System Vehicles Ground penetrating radar Modems Monitoring

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An adapted point based tracking for vehicle speed estimation in linear spacing

An adapted point based tracking for vehicle speed estimation...

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International Conference on computer and Communication engineering, ICCCE

Vehicle velocity estimation is an important aspect of intelligent transportation systems. Normally velocity is estimated using dedicated laser speed traps and Doppler radars. Recently, the use of cameras is becoming more common for the purpose of traffic surveillance and smart surveillance system. It is thus the aim of this paper to propose a method for vehicle speed estimation using these existing video cameras. In this paper, we propose a vehicle speed estimation method from video analysis. The method proposed contains several steps; image preprocessing, centroid extraction and tracking. The proposed method transforms the 2D image points into a 3D virtual world to obtain actual vehicle position in 3D space. This is to account for perspective distortion commonly seen in images. Using these 3D points and measuring the time for displacement, the vehicle speed is obtained. Experimental results have shown that the proposed method gives accurate velocity estimation.

关键词： Vehicles Estimation Surveillance Tracking Pixel Cameras Three dimensional displays

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