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20th IEEE Conference on Signal processing - algorithms, Architectures, Arrangements, and Applications (SPA)

作者： Konieczka, Adam Piniarski, Karol Balcerek, Julian Poznan Univ Tech Chair Control & Syst Engn Div Signal Proc & Elect Syst Poznan Poland

ISBN: (纸本)9788362065271

In this paper the application for generation of HDR image based on two consecutive images (underexposed and overexposed) for Android mobile operating system is presented. The implemented software preserves a lot of image details and maintains a low execution time. These features are particularly important for pictures taken using mobile devices in emergency situations. Such photos may constitute evidence that a threat occurred, was properly recognized, or someone committed a crime. HDR images can be also used in mobile systems for supporting pedestrians or drivers. Obtained results indicate on a high effectiveness of the presented solution.

关键词： HDR tonal mapping mobile device image processing threat recognition

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Plant high-throughput phenotyping using photogrammetry and imaging techniques to measure leaf length and rosette area

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2016年第0期127卷 376-394页

作者： An, Nan Palmer, Christine M. Baker, Robert L. Markelz, R. J. Cody Ta, James Covington, Michael F. Maloof, Julin N. Welch, Stephen M. Weinig, Cynthia Kansas State Univ Dept Agron Manhattan KS 66506 USA Univ Calif Davis Dept Plant Biol Davis CA 95616 USA Univ Wyoming Dept Bot Laramie WY 82071 USA

Plant phenotyping is central to understand causal effects of genotypes and environments on trait expression and is a critical factor in expediting plant breeding. Previously, plant phenotypic traits were quantified using invasive, time-consuming, labor-intensive, cost-inefficient, and often destructive manual sampling methods that were also prone to observer error. In recent years, photogrammetry and image processing techniques have been introduced to plant phenotyping, but cost efficiency issues remain when combining these two techniques within large-scale plant phenotyping studies. Using these high throughput techniques in basic plant biology research and agriculture are still in the developmental stages but show great promise for rapid phenotyping, which will materially aid both science and crop improvement efforts. In this study, we introduce an automated high-throughput phenotyping pipeline using affordable imaging systems and image processing algorithms to build 2D mosaicked orthophotos. Chamber-based and ground-level field implementations are used to measure phenotypic traits such as leaf length and rosette area in 2D images. Our automated pipeline has cross-platform capabilities and a degree of instrument independence, making it suitable for various situations. (C) 2016 Elsevier B.V. All rights reserved.

关键词： High-throughput Phenotyping Photogrammetry image processing Shade avoidance Arabidopsis thaliana

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Adaptive guided image filter for warping in variational optical flow computation

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SIGNAL processing 2016年 127卷 253-265页

作者： Tu, Zhigang Poppe, Ronald Veltkamp, Remco C. Arizona State Univ Sch Comp Informat Decis Syst Engn Tempe AZ 85287 USA Univ Utrecht Dept Informat & Comp Sci Utrecht Netherlands

The variational optical flow method is considered to be the standard method to calculate an accurate dense motion field between successive frames. It assumes that the energy function has spatiotemporal continuities and appearance motions are small. However, for real image sequences, the temporal continuity assumption is often violated due to outliers and occlusions, causing inaccurate flow vectors at these regions. After each warping operation, errors are generated at the corresponding regions of the warped interpolation image. This results in an inaccurate discrete approximation of the temporal derivative and thus ends up affecting the accuracy of the estimated flow field. In this paper, we propose an adaptive guided image filter to correct these errors in the warped interpolation image. A guidance image is reconstructed by considering both the feature of the reference image as well as the difference between the warped interpolation image and the reference image, to guide the filtering of the warped interpolation image. To adjust the smoothing degree, the regularization parameter in the guided image filter is adaptively selected based on a confidence measure. Extensive experiments on different datasets and comparison with state-of-the-art variational optical flow algorithms demonstrate the effectiveness of our method. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Variational optical flow Warped interpolation image correction Adaptive guided image filter

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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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systems AND METHODS FOR MACHINE-GENERATED AVATARS

SYSTEMS AND METHODS FOR MACHINE-GENERATED AVATARS

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作者： SCHOLAR, Wayne

标准号: WO2017075452(A1)

systems and methods are disclosed for creating a machine generated avatar. A machine generated avatar is an avatar generated by processing video and audio information extracted from a recording of a human speaking a reading corpora and enabling the created avatar to be able to say an unlimited number of utterances, i.e., utterances that were not recorded. The video and audio processing consists of the use of machine learning algorithms that may create predictive models based upon pixel, semantic, phonetic, intonation, and wavelets.

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A cooperative semi-supervised fuzzy clustering framework for dental X-ray image segmentation

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EXPERT systems WITH APPLICATIONS 2016年 46卷 380-393页

作者： Le Hoang Son Tran Manh Tuan Ton Duc Thang Univ Div Data Sci Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Informat Technol Ho Chi Minh City Vietnam Thai Nguyen Univ Coll Informat & Commun Technol Quyet Thang Thai Nguyen Vietnam

Dental X-ray image segmentation (DXIS) is an indispensable process in practical dentistry for diagnosis of. periodontitis diseases from an X-ray image. It has been said that DXIS is one of the most important and necessary steps to analyze dental images in order to get valuable information for medical diagnosis support systems and other recognition tools. Specialized data mining methods for DXIS have been investigated to achieve high accuracy of segmentation. However, traditional image processing and clustering algorithms often meet challenges in determining parameters or common boundaries of teeth samples. It was shown that performance of a clustering algorithm is enhanced when additional information provided by users is attached to inputs of the algorithm. In this paper, we propose a new cooperative scheme that applies semi-supervised fuzzy clustering algorithms to DXIS. Specifically, the Otsu method is used to remove the Background area from an X-ray dental image. Then, the FCM algorithm is chosen to remove the Dental Structure area from the results of the previous steps. Finally, Semi-supervised Entropy regularized Fuzzy Clustering algorithm (eSFCM) is opted to clarify and improve the results based on the optimal result from the previous clustering method. The proposed framework is evaluated on a real collection of dental X-ray image datasets from Hanoi Medical University, Vietnam. Experimental results have revealed that clustering quality of the cooperative framework is better than those of the relevant ones. The findings of this paper have great impact and significance to researches in the fields of medical science and expert systems. It has been the fact that medical diagnosis is often an experienced and case-based process which requests long time practicing in real patients. In many situations, young clinicians do not have chance for such the practice so that it is necessary to utilize a computerized medical diagnosis system which could simulate medical proce

关键词： Dental image segmentation Fuzzy clustering Performance assessment Semi-supervised fuzzy clustering X-ray images

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A Survey of Blob Detection algorithms for Biomedical images 7

A Survey of Blob Detection Algorithms for Biomedical Images

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7th International Conference on Information Communication Technology for Embedded systems (IC-ICTES)

作者： Han, Kay Thwe Min Uyyanonvara, Bunyarit Thammasat Univ Sirindhorn Int Inst Technol Sch Informat Comp & Commun Technol 131 Moo 5 Bangkadi 12000 Muang Pathumtha Thailand

ISBN: (纸本)9781509022489

This paper presents a survey of blob detection methods which has been applied on image processing with relation of medical images proposed by literature. "The blob detection is a mathematical method which detects regions or points in digital images". [1] The regions or points which have noticeable difference with their surroundings is called blob. Given the increased interest in biomedical image processing system, many algorithms and methods have been reported to apply but there is no systematic survey and classification of the blob detection for medical images and how they have been assessed and applied. The findings, which is the most usable methods of blob detectors in biomedical image processing has been presented. It was also investigated how these studies have been surveyed, how they evolved in the main digital libraries over the last decade, and what points deserves further attention, through new research. From this survey, practitioners and researchers can adopt the blob detection methods and analyze to use these methods in their research for further development.

关键词： Blob Detection Survey Medical image processing Blob Detection Methods

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A robust noise removal algorithm with consideration of contextual information

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MULTIDIMENSIONAL systems AND SIGNAL processing 2016年第1期27卷 179-200页

作者： Chen, Qing-Qiang Chang, Chuan-Yu Fujian Univ Technol Sch Informat Sci & Engn Fuzhou Peoples R China Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn Touliu 64002 Yunlin Taiwan

This paper analyzes an image noise model of additive positive and negative impulses that often appear in practical applications. Based on the characteristic that any pixel in an undisturbed image is similar to its neighbors, a local pixel correlation coefficient is proposed. For a pixel, based on the number of similar pixels in its neighborhood, the probability of whether it is noisy or normal can be accurately calculated. An adaptive masking weighted mean filter with consideration of contextual information is proposed to filter noise while retaining the edge details of the image. The proposed algorithm does not require any initial parameters or threshold values to be set. Experimental results show that the proposed algorithm is applicable to the proposed noise model and that the proposed noise filtering is significantly better than that of existing algorithms.

关键词： Impulse noise image denoising Contextual information Median filter

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Land use mapping from CBERS-2 images with open source tools by applying different classification algorithms

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PHYSICS AND CHEMISTRY OF THE EARTH 2016年 91卷 27-37页

作者： Sanhouse-Garcia, Antonio J. Rangel-Peraza, Jesus Gabriel Bustos-Terrones, Yaneth Garcia-Ferrer, Alfonso Mesas-Carrascosa, Francisco J. Univ Cordoba Escuela Tecn Super Ingn Agron & Montes Dept Ingn Graf & Geomat Campus RabanalesN-4Km 396 E-14071 Cordoba Spain Inst Tecnol Culiacan Div Estudios Posgrad & Invest Ingn Ambiental Juan de Dios Batiz 310 Culiacan 80220 Sinaloa Mexico

Land cover classification is often based on different characteristics between their classes, but with great homogeneity within each one of them. This cover is obtained through field work or by mean of processing satellite images. Field work involves high costs;therefore, digital image processing techniques have become an important alternative to perform this task. However, in some developing countries and particularly in Casacoima municipality in Venezuela, there is a lack of geographic information systems due to the lack of updated information and high costs in software license acquisition. This research proposes a low cost methodology to develop thematic mapping of local land use and types of coverage in areas with scarce resources. Thematic mapping was developed from CBERS-2 images and spatial information available on the network using open source tools. The supervised classification method per pixel and per region was applied using different classification algorithms and comparing them among themselves. Classification method per pixel was based on Maxver algorithms (maximum likelihood) and Euclidean distance (minimum distance), while per region classification was based on the Bhattacharya algorithm. Satisfactory results were obtained from per region classification, where overall reliability of 83.93% and kappa index of 0.81% were observed. Maxver algorithm showed a reliability value of 73.36% and kappa index 0.69%, while Euclidean distance obtained values of 67.17% and 0.61% for reliability and kappa index, respectively. It was demonstrated that the proposed methodology was very useful in cartographic processing and updating, which in turn serve as a support to develop management plans and land management. Hence, open source tools showed to be an economically viable alternative not only for forestry organizations, but for the general public, allowing them to develop projects in economically depressed and/or environmentally threatened areas. (C) 2015 Elsevier Ltd

关键词： Geographic information systems Free software Digital image processing Land use classification Forest management Territorial administration

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Investigation on slice direction dependent detectability of volumetric cone beam CT images

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OPTICS EXPRESS 2016年第4期24卷 3749-3764页

作者： Han, Minah Lee, Changwoo Park, Subok Baek, Jongduk Yonsei Univ Sch Integrated Technol Inchon South Korea Yonsei Univ Yonsei Inst Convergence Technol Inchon South Korea US FDA Silver Spring MD USA

We investigate the detection performance of transverse and longitudinal planes for various signal sizes (i.e., 1 mm to 8 mm diameter spheres) in cone beam computed tomography (CBCT) images. CBCT images are generated by computer simulation and images are reconstructed using an FDK algorithm. For each slice direction and signal size, a human observer study is conducted with a signal-known-exactly/background-known-exactly (SKE/BKE) binary detection task. The detection performance of human observers is compared with that of a channelized Hotelling observer (CHO). The detection performance of an ideal linear observer is also calculated using a CHO with Laguerre-Gauss (LG) channels. The detectability of high contrast small signals (i.e., up to 4-mm-diameter spheres) is higher in the longitudinal plane than the transverse plane. It is also shown that CHO performance correlates well with human observer performance in both transverse and longitudinal plane images. (C) 2016 Optical Society of America

关键词： Computer simulation image processing algorithms image quality image quality assessment Imaging systems Reconstruction algorithms

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