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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems"

共 12675 条记录，以下是4481-4490 订阅

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Comparison of noise removal algorithms on Optical Coherence Tomography (OCT) image

Comparison of noise removal algorithms on Optical Coherence ...

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2016 IEEE International conference on Imaging systems and Techniques, IST 2016

作者： Shah, Asim Altaf Mohsin Malik, M. Usman Akram, M. Bazaz, Shafaat A. Department of Electrical Engineering Bahria University Islamabad Pakistan Department of Computer Engineering NUST Rawalpindi Pakistan Department of Computer Sciences CASE Islamabad Pakistan

ISBN: (纸本)9781509018178

Automatic Identification of disease through image processing in biomedical field is the norm of modern era. Ophthalmologists have used several invasive and noninvasive techniques for early detection of disease. OCT is one such noninvasive modality that performs high resolution tomographic imaging in biological systems. OCT images are produced containing speckle noise. Noise is a major factor that decreases image quality, hence degrading performance of noise image processing algorithms. It is therefore at highest priority to apply effective method for denoising image, before further processing. In this paper we applied Wavelet denoising, bilateral and wiener filter on an OCT images and discuss benefits and drawback of each algorithms. The effectiveness of each algorithm is compared on basis of Signal to noise ratio SNR, peak signal to noise ratio PSNR and Mean square error MSE. © 2016 IEEE.

关键词： image denoising

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QUANTITATIVE STUDY OF image FEATURES OF CLUSTERED MICROCALCIFICATIONS IN FOR-PRESENTATION MAMMOGRAMS 23

QUANTITATIVE STUDY OF IMAGE FEATURES OF CLUSTERED MICROCALCI...

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23rd IEEE International conference on image processing (ICIP)

作者： Wang, Juan Yang, Yongyi Nishikawa, Robert M. Illinois Inst Technol Dept Elect & Comp Engn Chicago IL 60616 USA Univ Pittsburgh Dept Radiol Pittsburgh PA 15213 USA

ISBN: (纸本)9781467399616

Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis (CAD) of breast cancer. In this study, we investigate the feasibility of using "for-presentation" format of FFDM (which are more readily available) in development of CAD algorithms for microcalcification (MC) lesions. We conduct a quantitative evaluation of both the image features and the detectability of individual MCs on a set of 188 mammograms acquired in both formats. The results demonstrate that there is a high degree of agreement in the image features between the two image formats, and that a slight increase in false-positives in MC detection is observed in for-presentation images.

关键词： Computer-aided diagnosis (CAD) full-field digital mammography (FFDM) microcalcifications

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Handwriting Recognition System for South Indian Languages - A Technical Review

Handwriting Recognition System for South Indian Languages - ...

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International conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Keerthi Prasad G. Vinay Hegde Asha K. Krishnappa H.K. GMIT Davanagere INDIA RVCE Bangalore INDIA

Handwriting recognition is the most popular area of research which provides major contribution to the trending technology - mobile computing. This paper provides technical details for the implementation of Handwriting recognition system. The techniques suitable for offline and online handwriting recognition system are also discussed. Some of the pre-processing and classification algorithms like normalization; re-sampling, Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW) are presented in this paper.

关键词： Handwriting recognition Character recognition Principal component analysis Feature extraction image recognition Time series analysis conferences

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A Novel image Encryption Algorithm Based on Multiple Chaotic systems and Self-adaptive Model 1

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4th International conference on Communications, Signal processing, and systems (CSPS)

作者： Wang, Chengqi Zhang, Xiao Zheng, Zhiming Beihang Univ Minist Educ Key Lab Math Informat & Behav Semant Beijing 100191 Peoples R China Beihang Univ Sch Math & Syst Sci Beijing 100191 Peoples R China

ISBN: (数字)9783662498316

ISBN: (纸本)9783662498316;9783662498293

In recent years, image encryption has attracted much attention. Particularly, due to large data capacity and high correlation among pixels, chaos-based image encryption algorithms are more suitable to be applied in the digital image encryption. In this paper, we propose a novel chaotic image encryption algorithm, in which novel multiple chaotic systems and efficient self-adaptive model are initially mingled to enhance the security. Different from conventional algorithms, plaintext participates in the generation of cryptograph in a new way, which follows the idea from the perceptron model. The proposed algorithm enlarges the key space, enhances the randomness of the algorithm, and resists the differential attack effectively. Simulation results are demonstrated that proposed algorithm possesses the high security for the main current attacks, which is an excellent candidate for practical applications of image encryption.

关键词： image encryption Multiple chaotic systems Self-adaptive model Perceptron model

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Estimating vital signs through non-contact video-based approaches: A survey

Estimating vital signs through non-contact video-based appro...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Ruchika Sinhal Kavita Singh Anuraj Shankar Department of CSE DMIETR Wardha India Department of CT YCCE Nagpur India HSPH Boston USA

ISBN: (纸本)9781509047611;9781509047604

The human body exhibits many vital signs, such as heart rate (HR) and respiratory rate (RR) used to assess fitness and health. Vital signs are typically measured by a trained health professional and may be difficult for individuals to accurately measure at home. Clinic visits are therefore needed with associated burdens of cost and time spent waiting in long queues. The widespread use of smart phones with video capability presents an opportunity to create non-invasive applications for assessment of vital signs. Over the past decade, several researchers have worked on assessing vital signs from video, including HR, RR and other parameters such as anemia and blood oxygen saturation (SpO2). This paper reviews the different image and video processing algorithms developed for vital signs assessment through non-contact methods, and outline the key remaining challenges in the field which can be used as potential research topics. The CHROM algorithm produces highest accuracy in detecting the signals from rPPG. There are different challenges of handling large database and motion stabilization which is not provided by any algorithm, this is main area of research in rPPG.

关键词： Monitoring Heart rate Biomedical monitoring Cameras Skin Face Blood

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Real-Time Geometric Scene Estimation for RGBD images using a 3D Box Shape Grammar

Real-Time Geometric Scene Estimation for RGBD Images using a...

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conference on Three-Dimensional Imaging, Visualization, and Display

作者： Willis, Andrew R. Brink, Kevin M. Univ North Carolina Charlotte 9201 Univ City Blvd Charlotte NC 28223 USA Air Force Res Lab Munit Directorate Eglin AFB FL 32542 USA

ISBN: (纸本)9781510601086

This article describes a novel real-time algorithm for the purpose of extracting box-like structures from RGBD image data. In contrast to conventional approaches, the proposed algorithm includes two novel attributes: (1) it divides the geometric estimation procedure into subroutines having atomic incremental computational costs, and (2) it uses a generative "Block World" perceptual model that infers both concave and convex box elements from detection of primitive box substructures. The end result is an efficient geometry processing engine suitable for use in real-time embedded systems such as those on an UAVs where it is intended to be an integral component for robotic navigation and mapping applications.

关键词： Data modeling 3D modeling 3D modeling image segmentation 3D image processing 3D image processing Robotics 3D metrology Detection and tracking algorithms image processing algorithms and systems Cameras image processing

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Genetic Algorithm-based Optimization of ELM for On-line Hyperspectral image Classification

Genetic Algorithm-based Optimization of ELM for On-line Hype...

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International Joint conference on Neural Networks

作者： J. Echanobe I. del Campo Victoria Martinez K. Basterretxea Dep. Electricity and Electronics University of the Basque Country (UPV/EHU) Leioa Basque Country Spain Dep. Electronic Technology University of the Basque Country (UPV/EHU) Bilbao Basque Country Spain

ISBN: (纸本)9781509061839

Hyperspectral remote sensing is becoming an active research field in the last decades thanks to the availability of efficient machine learning algorithms and also to the ever-increasing computation power. However, there exist application domains (e.g., embedded applications) in which the deployment of this kind of systems becomes unfeasible due to the high requirements related to the size, power consumption or processing speed. A way to overcome this trouble consists on using any method able to scale-down the dimensionality of the problem and/or to reduce the complexity of the machine learning models. In this paper, we propose the use of a multiobjective genetic algorithm to minimize both the dimension of the input space and the size of the machine learning model. In particular, we have developed a hyperspectral image classifier based on an Extreme Learning Machine (ELM) for which the number of system inputs (dimensionality) and the number of hidden neurons are minimized without decreasing its performance. The system is evaluated by using a known benchmark dataset.

关键词： Genetic algorithms Hyperspectral imaging Neurons Classification algorithms Optimization Algorithm design and analysis

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Near Duplicate image Matching Techniques

Near Duplicate Image Matching Techniques

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International conference on Information Communication and Embedded systems (ICICES)

作者： Landge, Amruta Mane, Pranoti MESCOE E&TC Pune Maharashtra India

ISBN: (纸本)9781509025527

Near duplicate image detection needs the matching of a bit altered images to the original image. This will help in the detection of forged images. A great deal of effort has been dedicated to visual applications that need efficient image similarity metrics and signature. Digital images can be easily edited and manipulated owing to the great functionality of image processing software. This leads to the challenge of matching somewhat altered images to their originals, which is termed as near duplicate image detection. This paper discusses the literature reviewed on the development of several image matching algorithms. This paper encompasses 2 sections. Section 1 is the introduction. Section 2 discusses the literature reviewed on the development of image matching algorithms.

关键词： near-duplicate images near-duplicate image retrieval near-duplicate image detection

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image encryption in code based compression algorithms based on multilevel image structure model

Image encryption in code based compression algorithms based ...

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International conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Sergey Bezzateev Natalia Voloshina Saint Petersburg University of Aerospace Instrumentation ITMO University St. Petersburg Russia

image compression is a widely adopted technique used for effective image storage and transmission over open communication channels in cyber-physical systems. Standard cryptographic algorithms are usually used to reach this goal. Therefore, in order to organize effective and secure storage of images it is required to follow two independent and sequential procedures - compression and encryption. In the scenario of interest, it is needed to do compression and encryption transformations in reverse order to restore the original image, i.e. it is necessary to have a so-called “code book” similarly as for encryption and decryption to have a secret key. An effective way of combining these procedures for digital images is proposed in this manuscript. This research is mainly focused on the compression methods that consider significance of the initial multimedia object (for example image) different parts to increase the quality of resulting (decompressed) image. One of the most effective approaches for this task is to utilize error-correcting codes (ECC) that allow to limit the number of resulting errors (distortion) as well as to ensure the value of resulting compression ratio. Application of such codes enable to distribute errors that are added during the processing procedure according to predefined significance of the initial multimedia object elements. The approach that is based on weighted Hamming metric that makes it possible to guaranty the limitation of maximum error number (distortions) that takes into consideration predefined significance of the image zones is represented as an example. The way to use subclass of Goppa codes perfect in weighted Hamming metric when Goppa polynomials are used as a secret key is presented as well. The additional effect of such encrypted compression methods is auto-watermarking of the resulting image.

关键词： image coding Distortion Measurement Error correction codes Encryption Decoding Communication channels

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HDSVM: A High Efficiency Distributed SVM Framework over Data Stream

HDSVM: A High Efficiency Distributed SVM Framework over Data...

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IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Yan Hou Yijie Wang Xingkong Ma Li Cheng College of Computer National University of Defense Technology Changsha National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)9781538637913

The application of Support Vector Machine (SVM) over data stream is growing with the increasing real-time processing requirements in classification field, like anomaly detection and real-time image processing. However, the dynamic live data with high volume and fast arrival rate in data streams make it challenging to apply SVM in data stream processing. Existing SVM implementations are mostly designed for batch processing and hardly satisfy the efficiency requirement of stream processing for its inherent complexity. To address the challenges, we propose a high efficiency distributed SVM framework over data stream (HDSVM), which consists of two main algorithms, incremental learning algorithm and distributed algorithm. Firstly, we propose a partial support vectors reserving incremental learning algorithm (PSVIL). By selecting a subset of support vectors based on their distances to classification hyperplane instead of the universal set to update SVM, the algorithm achieves lower time overhead while ensuring accuracy. Secondly, we propose a distribution remaining partition and fast aggregation distributed algorithm (DRPFA) for SVM. The real-time data is partitioned based on the original distribution with clustering instead of random partition, and historical support vectors are partitioned based on their distances to the classification hyperplane. The global hyperplane can be obtained by averaging the parameters of local hyperplanes due to the above partition strategy. Extensive experiments on Apache Storm show that the proposed HDSVM achieve lower time overhead and similar accuracy compared with the state-of-art. Speed-up ratio is increased by 2-8 times within 1% accuracy deviation.

关键词： Support vector machines Training Distributed databases Distributed algorithms Real-time systems Partitioning algorithms Streaming media

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