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Conference on image processing - algorithms and systems XIII

作者： Rubel, Aleksey S. Lukin, vladimir v. Egiazarian, Karen O. Natl Aerosp Univ UA-61070 Kharkov Ukraine Tampere Univ Technol FIN-33101 Tampere Finland

ISBN: (纸本)9781628414899

Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HvS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

关键词： denoising prediction grayscale images DCT and BM3D filter fitting

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Comparison of Citrus Fruit Diseases Revealing with Data Mining and image processing Techniques based on Assorted Parameters 5

Comparison of Citrus Fruit Diseases Revealing with Data Mini...

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International Conference on Computer Communication and Informatics ICCCI

作者： Devi, M. Renuka Kavitha, v. SNS Coll Technol Coimbatore Tamil Nadu India Bharathiar Univ Coimbatore Tamil Nadu India

ISBN: (纸本)9781479968053

Machine vision has become a key technology in the area of quality control. "vision systems" is primarily focused on computer vision in the context of inspection of the products such as food, pharmaceuticals. The system can consist of a number of cameras all capturing, interpreting and signaling individually with a control system related to some predefined algorithms. The analysis of citrus fruits using various assorted parameters revealing the diseases afflicting Citrus fruits and isolation of the same using image processing and Data Mining Techniques is the core area discussed here with.

关键词： Citrus Fruit Machine vision Computer vision image processing Data Mining

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Normalization of images from geostationary earth remote sensing systems

Normalization of images from geostationary earth remote sens...

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2015 5th International Workshop on Computer Science and Engineering: Information processing and Control Engineering, WCSE 2015-IPCE

作者： Egoshkin, N. Eremeev, v. Ryazan State Radio Engineering University Gagarin Str. 59/1 Ryazan390005 Russia

This paper considers models and algorithms of normalization of images obtained from geostationary remote sensing systems. And the paper suggests and researches algorithms of geometrical distortion correction and transformation of images into the standard Normalized Geostationary Projection. The algorithm of geodetic connection adjustment with usage of Earth contour points in the image was developed. Practical testing of algorithms in the images obtained from the Russian spacecraft "Elektro-L" was executed.

关键词： Geostationary satellites

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Autofocusing SAR images using multistage wienerfilter

Autofocusing SAR images using multistage wienerfilter

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IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

作者： Shruthi B Satyaprasad Avinash Ravi Koushik R Rajesh Reena Sharma Department of Telecommunication R V College of Engineering Bangalore India Defence R&D Organisation Center for Airbrone Systems Bangalore India

ISBN: (纸本)9781509007752

Synthetic Aperture Radars (SAR) provide high resolution ground images by utilizing the aircraft motion to synthesize a large aperture. The presence of residual phase error in the SAR images causes defocusing in the images. Autofocus algorithm compensates these phase errors to obtain a focused image. In most scenarios a priori information about the type of phase error is known which can be effectively utilized in autofocus techniques. The paper proposes a new autofocus algorithm which is based on Wiener filter theory and implements a multistage Wiener filter to compensate the phase error in SAR images.

关键词： Wiener filters Synthetic aperture radar Signal processing algorithms Wideband Apertures Measurement

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A prototype 1024 electrode embedded computer based Epiretinal Prosthesis System

A prototype 1024 electrode embedded computer based Epiretina...

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International Conference on Signal processing and Integrated Networks (SPIN)

作者： N. Sharmili v. Bhujanga Rao P. Seetharamaiah N. Swapna Dept. of Computer Science and Engg. VIIT Visakhapatnam India Defense R&D Organization DRDO New Delhi India Dept. of Computer Science and Systems Engg. Andhra University Visakhapatnam India Dept. of Computer Science and Engg. RIET Rajahmundry India

ISBN: (纸本)9781467391986

Epiretinal prosthesis is a biomedical implant technology currently being developed around the world in hopes of restoring useful vision for patients suffering from retinal degenerative diseases such as Age-related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP). Epiretinal Prosthesis System (EPS) consists of four parts that includes Body Worn image Processor (BWIP), Retinal Implantable Receiver Stimulator (RIRS), wireless telemetry and electrode array. images are captured by BWIP's camera and encoded into a 1 Mbps bit stream by BWIP. The bit stream is modulated on 8.195 MHz carrier and transmitted serially to RIRS through wireless telemetry. RIRS converts the bit stream into electrical pulses and drives 1024 electrode array to stimulate the survival parts of retina electrically with visual cues for understanding the video picture/image. This paper presents the design of flexible high resolution 1024- electrode embedded computer based EPS using embedded computer based efficient control algorithms for better visual prediction. Finally, the integrity of the EPS has been verified visually through video display on LCD/LED array. The experimental results of EPS are enumerated for the object of human face using 1024-electrode/pixel LED array.

关键词： Prosthetics Electrodes Retina Wireless communication Streaming media Telemetry Radio frequency

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A Novel Approach to the Extraction of Multiple Salient Objects in an image

A Novel Approach to the Extraction of Multiple Salient Objec...

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IEEE International Conference on Signal processing, Informatics, Communication and Energy systems (SPICES)

作者： Muralidharan, Srikanth vasudevan, Arun Balajee Pratheek, Chintapalli Shiva Raman, Shanmuganathan Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada Ecole Polytech Fed Lausanne Sch Comp & Commun Sci CH-1015 Lausanne Switzerland Indian Inst Technol Jodhpur Elect Engn Jodhpur Rajasthan India Indian Inst Technol Gandhinagar Elect Engn Gandhinagar India

ISBN: (纸本)9781479918232

This paper describes a novel approach for extraction of multiple objects from a given image of a natural scene. In the proposed approach, multiple objects are extracted by the application of saliency detection on the image. We use two distinct approaches for object extraction. One approach uses superpixels on the saliency map. Then the intensity of saliency map in each superpixel is used to compute distance between the centres of superpixels. These act as constraints to extract the objects from the image. The other approach is the application of Active Contour model on the saliency map and estimating a bounding box on the intermediate binary image result extracts the objects in the image. The approach is unique in its way of extracting objects from a scene containing multiple objects as it does not use extensive image search like the existing algorithms and therefore leads to a fast and simple extraction.

关键词： Superpixels

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Wound image evaluation with machine learning

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NEUROCOMPUTING 2015年 164卷 112-122页

作者： veredas, Francisco J. Luque-Baena, Rafael M. Martin-Santos, Francisco J. Morilla-Herrera, Juan C. Morente, Laura Univ Malaga Dept Lenguajes & Ciencias Comp E-29071 Malaga Spain Univ Extremadura Ctr Univ Merida Dept Ingn Sist Informat & Telemat Merida 00680 Spain Junta Andalucia Serv Andaluz Salud Malaga 29001 Spain Diputac Malaga Escuela Univ Enfermeria Malaga 29071 Spain

A pressure ulcer is a clinical pathology of localized damage to the skin and underlying tissue caused by pressure, shear or friction. Diagnosis, care and treatment of pressure ulcers can result in extremely expensive costs for health systems. A reliable diagnosis supported by precise wound evaluation is crucial in order to succeed on the treatment decision and, in some cases, to save the patient's life. However, current clinical evaluation procedures, focused mainly on visual inspection, do not seem to be accurate enough to accomplish this important task. This paper presents a computer-vision approach based on image processing algorithms and supervised learning techniques to help detect and classify wound tissue types that play an important role in wound diagnosis. The system proposed involves the use of the k-means clustering algorithm for image segmentation and compares three different machine learning approaches neural networks, support vector machines and random forest decision trees to classify effectively each segmented region as the appropriate tissue type. Feature selection based on a wrapper approach with recursive feature elimination is shown to be effective in keeping the efficacy of the classifiers up and significantly reducing the number of necessary predictors. Results obtained show high performance rates from classifiers based on fitted neural networks, random forest models and support vector machines (overall accuracy on a testing set [95% Cl], respectively: 81.87% [80.03%, 83.61%];87.37% [85.76%, 88.86%];88.08% [86.51%, 89.53%]), with significant differences found between the three machine learning approaches. This study seeks to provide, using standard classification algorithms, a consistent and robust methodological framework as a basis for the development of reliable computational systems to support ulcer diagnosis. (C) 2015 Elsevier B.v. All rights reserved.

关键词： Machine vision Medical imaging Computer-aided diagnosis Wound evaluation

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A BRIEF-Gist Based Efficient Place Recognition for Indoor Home Service Robots

A BRIEF-Gist Based Efficient Place Recognition for Indoor Ho...

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International Conference on Control, Automation and systems

作者： Yurim Jeon Taejae Lee Chulhong Kim Donghoon Yi Dong-Il "Dan" Cho Department of Electrical Engineering and Computer Science Seoul National University Automation and Systems Research Institute (ASRI) and Department of Electrical Engineering and Computer Science Seoul National University ASRI Inter-university Semiconductor Research Center (ISRC) and Department of Electrical Engineering and Computer Science Seoul National University

ISBN: (纸本)9781467390583

visual place recognition has been vastly researched in the last decade. Most of the previous works have concentrated on improvement of performance when the environment changes due to illumination, weather or season at outdoor with abundant features and textures for place recognition. On the other hand, when a robot moves in a home environment, input images sometimes contain less features or textures for place recognition, which in turn degrades the precision and recall performance. This paper presents an efficient place recognition method based on a binary robust independent elementary features gist (BRIEF-Gist) descriptor for indoor home service robot. The proposed method simply extracts multiple BRIEF-Gist descriptors from an input image, which results in a higher performance. A simple data structure for fast comparison between images is also presented. In home environment experiments, the original BRIEF-Gist and the proposed method shows the maximum recall rate of 1.6% and 9.7%, respectively, both with a precision of 100%. On the other hand, local feature based DLoopDetector method shows below 5% of both recall and precision performance. For comparison, computation times, which are the average execution times for processing place recognition algorithms of one image with 2058 places in a map, are measured;the proposed method without the proposed data structure takes 31.4 ms, and the proposed method with the proposed data structure takes 10.5 ms.

关键词： Place recognition BRIEF-GIST

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Information Theory-Based Detection of Noisy Bit Planes in Medical images

Information Theory-Based Detection of Noisy Bit Planes in Me...

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Brazilian Symposium on Computer Graphics and image processing (SIBGRAPI)

作者： Hugo N. De Oliveira Jefersson Alex Dos Santos Matheus C. de Melo Thaís G. do Rêgo Leonardo v. Batista Universidade Federal de Minas Gerais Belo Horizonte MG BR Centro de Inf. Universidade Federal da Paraiba Joao Pessoa PB BR Centro de Inf. Universidade Federal da Paraíba João Pessoa Brazil

ISBN: (纸本)9781509035694;9781509035687

Mammographic Computer-Aided Diagnosis systems are applications designed to assist radiologists in diagnosis of malignancy in mammographic findings. Most methods described in the literature do not perform a proper preprocessing step in mammographic images prior to classification, which can generate inconsistent results due to the potentially large amount of noise in medical images. This paper proposes a new method based on Information Theory and Data Compression for detection of random noise in image bit planes. In order to validate the efficiency of the proposed noise removal method, we used Machine Learning algorithms to classify mammographic findings from the Digital Database for Screening Mammography. Results using texture features indicate that a reduction in the radiometric resolution of 4 or 5 bit planes in digitized screen film mammographic images result in a better classification performance.

关键词： Breast cancer Mammography Delta-sigma modulation Entropy Noise measurement Context

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Benchmarking of objective quality metrics for HDR image quality assessment

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EURASIP JOURNAL ON image AND vIDEO processing 2015年第1期2015卷 1-18页

作者： Hanhart, Philippe Bernardo, Marco v. Pereira, Manuela Pinheiro, Antonio M. G. Ebrahimi, Touradj Ecole Polytech Fed Lausanne Multimedia Signal Proc Grp CH-1015 Lausanne Switzerland UBI Opt Ctr Covilha Portugal UBI Inst Telecomunicacoes Covilha Portugal

Recent advances in high dynamic range (HDR) capture and display technologies have attracted a lot of interest from scientific, professional, and artistic communities. As in any technology, the evaluation of HDR systems in terms of quality of experience is essential. Subjective evaluations are time consuming and expensive, and thus objective quality assessment tools are needed as well. In this paper, we report and analyze the results of an extensive benchmarking of objective quality metrics for HDR image quality assessment. In total, 35 objective metrics were benchmarked on a database of 20 HDR contents encoded with 3 compression algorithms at 4 bit rates, leading to a total of 240 compressed HDR images, using subjective quality scores as ground truth. Performance indexes were computed to assess the accuracy, monotonicity, and consistency of the metric estimation of subjective scores. Statistical analysis was performed on the performance indexes to discriminate small differences between metrics. Results demonstrated that metrics designed for HDR content, i.e., HDR-vDP-2 and HDR-vQM, are the most reliable predictors of perceived quality. Finally, our findings suggested that the performance of most full-reference metrics can be improved by considering non-linearities of the human visual system, while further efforts are necessary to improve performance of no-reference quality metrics for HDR content.

关键词： image quality assessment Objective metrics High dynamic range JPEG XT

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