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检索条件"任意字段=Conference on Image Algebra and Morphological Image Processing V"

共 656 条记录，以下是371-380 订阅

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Ortho-unitary transformations for color image processing

Ortho-unitary transformations for color image processing

引用

International Crimean conference on Microwave & Telecommunication Technology

作者： v.G. Labunets D.A. Berenov N.N. verbitskaia Ural'skij federal'nyj universitet imeni pervogo Prezidenta Rossii B N El'cina Ekaterinburg Sverdlovskaa ooblast' RU

A novel algebraic approach based on triplet 3D algebras for color image processing and recognition is under development. A family of discrete color-valued fast transformations has been presented to be used for color i... 详细信息

关键词： Transforms image color analysis Color algebra Three-dimensional displays Region 8 Electronic mail

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Is the animal brain a Clifford algebra computer?

Is the animal brain a Clifford algebra computer?

引用

International Crimean conference on Microwave & Telecommunication Technology

作者： v.G. Labunets D.N. Gainanov D.A. Berenov Ural'skij federal'nyj universitet imeni pervogo Prezidenta Rossii B N El'cina Ekaterinburg Sverdlovskaa ooblast' RU

We present a new theoretical framework for multidimensional image processing using hypercomplex and Clifford algebras. The main goal of the work is to show that commutative hypercomplex algebras and Clifford algebras can be used to solve problems of hyperspectral, multi-color and color image processing and pattern recognition in a natural and effective manner. Thus, the animal brain might have the ability to operate as a Clifford algebra computing device.

关键词： algebra Animals Computers Electronic mail visualization Educational institutions Region 8

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2D image data approximation using Savitzky Golay filter — Smoothing and differencing

2D Image data approximation using Savitzky Golay filter — S...

引用

International Multi-conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)

作者： B Ganga Gowri v Hariharan S Thara v Sowmya S Sachin Kumar K. P. Soman Center For Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore-641112 India Center For Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore India

Smoothing and differencing is one of the major important and necessary step in the field of signal processing, image processing and also in the field on analytical chemistry. The search for an efficient image smoothing and edge detection method is a challenging task in image processing sector. Savitzky Golay Filters are one among the widely used filters for analytical chemistry. Even though they have exceptional features, they are rarely used in the field of image processing. The designed filter is applied for image smoothing and a mathematical model based on partial derivatives is proposed to extract the edges in images. The smoothing technique of SG filter offers an extremely simple aid in extracting the edge information. An approach using SG filter which can be applied in preserving edge information is one of the major tasks involved in the classification process in the domain of Optical Character Recognition. The paper is focused on designing the Savitzky Golay filter by using the concepts of linear algebra. The main objective of the paper is to portray a clear cut idea about Savitzky Golay filter and to study the design of Savitsky Golay filters based on the concepts of Linear algebra.

关键词： image edge detection vectors Smoothing methods Noise Polynomials Least squares approximations

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vECTOR MATHEMATICAL morphological OPERATORS BASED ON FUZZY EXTREMUM ESTIMATION

VECTOR MATHEMATICAL MORPHOLOGICAL OPERATORS BASED ON FUZZY E...

引用

IEEE International conference on image processing

作者： Tao Lei Yangyu Fan Chenrui Zhang Xiaopeng Wang School of Electronic and Information Engineering Lanzhou Jiao tong University Lanzhou China 730070 School of Electronics and Information Northwestern Polytechnical University Xi'an China 710072

ISBN: (纸本)9781479923427

Two fundamental problems in vector extremum estimation based on lexicographical ordering are investigated in this paper. The first problem is the choice of the optimal marginal components applying to lexicographical ordering. And the second is that the lexicographical ordering only depends on the first component which leads to the followed components taking no effect. To solve the two problems, three novel marginal components are presented by means of the quaternion description of a color image. Moreover, a new fuzzy extremum estimation algorithm (FEEA) is also proposed and applied to vector ordering. Comparing with the existing solutions, experimental results show that the proposed FEEA has better effect on vector extremum estimation, and the presented frame of vector mathematical morphology can be used to process color image and provide better result.

关键词： vector mathematical morphology color image processing quaternion decomposition lexicographical ordering Color image processing extremum values color image Cloning vectors Operators OPERATORS

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Segmentation of time-lapse images with focus on microscopic images of cells

Segmentation of time-lapse images with focus on microscopic ...

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17th International conference on image Analysis and processing, ICIAP 2013

作者： Soukup, Jindřich Císař, Petr Šroubek, Filip Charles University in Prague Ovocný trh 5 CZ-116 36 Prague 1 Czech Republic Institute of Information Theory and Automation of the ASCR Pod vodárenskou věží 4 CZ-182 08 Prague 8 Czech Republic University of South Bohemia in České Budějovice FFPW CENAKVA Husova tř. 458/102 CZ-370 05 České Budějovice Czech Republic

ISBN: (纸本)9783642411830

Phase contrast is a noninvasive microscopy imaging technique that is widely used in time-lapse imaging of cells. Resulting images however contain some optical artifacts, which makes automated processing by computer difficult. We developed a novel algorithm for cell segmentation. It is based on processing of time differences between images and combination of thresholding, blurring and morphological operations. We tested the algorithm on four different cell types acquired by two different microscopes. We evaluated the precision of segmentation against the manual segmentation by human operator and compared also with other methods. Our algorithm is simple, fast and shows accuracy that is comparable to manual segmentation. In addition it can correctly separate the dead from living cells. © 2013 Springer-verlag.

关键词： Cells

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A NOvEL MARKER-LESS TUMOR TRACKING STRATEGY ON LOW-RANK FLUOROSCOPIC imageS FOR image-GUIDED LUNG CANCER RADIOTHERAPY

A NOVEL MARKER-LESS TUMOR TRACKING STRATEGY ON LOW-RANK FLUO...

引用

IEEE International conference on image processing

作者： Wei Huang Jing Li Peng Zhang Min Wan School of Information Engineering Nanchang University China School of Computer Science Northwestern Polytechnical University China National Heart Centre SingHealth Singapore

ISBN: (纸本)9781479923427

Fluoroscopic images recording the real-time motion of lung tumor lesion play an important role on lung cancer radiotherapy, as these images help to facilitate the accurate delivery of radiation dose on target tumor lesion. Derivation of tumor position in conventional lung tumor tracking strategies is realized via either placing external surrogates on patients or implanting internal fiducial markers in patients. Inaccurate tumor tracking and patient safety problems are often inevitable for these strategies. In this study, a novel marker-less tumor tracking strategy is presented for image-guided lung cancer radiotherapy. A fluoroscopic image is first decomposed into low-rank and sparse components based on robust-PCA via a split Bregman method. Then, a series of techniques, including K-means clustering, morphological processing, connected component analysis, etc are employed on obtained low-rank fluoroscopic images for tumor tracking. Clinical data obtained from 45 patients is incorporated for experimental evaluation. Promising results are demonstrated from the introduced strategy.

关键词： Mark-less Tumor Tracking Fluoroscopic image Robust-PCA Split Bregman method image processing image processing images Radiation Dosage Lung Cancer Radiotherapy tracking Lung Neoplasms Fluoroscopic imaging Tumours cancer radiotherapy split and merge

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Is the animal brain a Clifford algebra computer?

Is the animal brain a Clifford algebra computer?

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2013 23rd International Crimean conference Microwave and Telecommunication Technology, CriMiCo 2013

作者： Labunets, v.G. Gainanov, D.N. Berenov, D.A. Ural Federal University Named after the First President of Russia B.N. Yeltsin 19 Mira Ave. Yekaterinburg Sverdlovsk region 620002 Russia

ISBN: (纸本)9789663354019

关键词： Pattern recognition

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A MODEL-BASED APPROACH FOR COMPOUND LEAvES UNDERSTANDING AND IDENTIFICATION

A MODEL-BASED APPROACH FOR COMPOUND LEAVES UNDERSTANDING AND...

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IEEE International conference on image processing

作者： Guillaume Cerutti Laure Tougne Julien Mille Antoine vacavant Didier Coquin Université de Lyon CNRS Clermont Université Université d'Auvergne ISIT F-63001 Clermont-Ferrand LISTIC Domaine Universitaire F-74944 Annecy le Vieux

ISBN: (纸本)9781479923427

In this paper, we propose a specific method for the identification of compound-leaved tree species, with the aim of integrating it in an educational smartphone application. Our work is based on dedicated shape models for compound leaves, designed to estimate the number and shape of leaflets. A deformable template approach is used to fit these models and produce a high-level interpretation of the image content. The resulting models are later used for the segmentation of leaves in both plain and natural background images, by the use of multiple region-based active contours. Combined with other botany-inspired descriptors accounting for the morphological properties of the leaves, we propose a classification method that makes a semantic interpretation possible. Results are presented over a set of more than 1000 images from 17 European tree species, and an integration in the existing mobile application Folia~1 is considered.

关键词： plant recognition compound leaf deformable templates image segmentation active contours classification Active contours image segmentation foliage Classification Methods images

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AUTOMATED SEGMENTATION OF MULTIPLE SCLEROSIS LESION IN INTENSITY ENHANCED FLAIR MRI USING TEXTURE FEATURES AND SUPPORT vECTOR MACHINE

AUTOMATED SEGMENTATION OF MULTIPLE SCLEROSIS LESION IN INTEN...

引用

IEEE International conference on image processing

作者： Pallab Kanti Roy Alauddin Bhuiyan Kotagiri Ramamohanarao Department of Computing and Information Systems The University of MelbourneAustralia.

ISBN: (纸本)9781479923427

In this paper, a fully automated segmentation method is proposed to identify Multiple Sclerosis (MS) related white matter lesions from brain magnetic resonance imaging (MRI) data. The main contribution of this paper is to obtain a new texture feature set for MS Lesion segmentation that is a combination of local and global neighbourhood information. The proposed method adopts a robust intensity normalization technique and lesion contrast enhancement filter for enhancing the region of interest. We use a Support vector Machine (SvM) to classify lesion pixels and level set based active contour and morphological filtering to achieve higher accuracy on lesion pixel identification. Quantitative evaluation of the proposed method is carried on real MRI data set provided by MS Lesion Challenge 2008. The results obtained from our method indicate significant improvement in performance compare to three state of the art methods that shows the proposed method's high suitability for assisting the neurologist to detect the MS in clinical practice.

关键词： Multiple Sclerosis MRI image Enhancement SvM image Segmentation Support vector Network Multiple Sclerosis image segmentation image enhancement Magnetic Resonance Imaging C7orf49 gene Automation hardening (materials) tristate machine Mass spectroscopy state of the art MS gene

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Pre-processing for Muscle Motion Analysis: Adaptive Guided image Filtering for Speckle Reduction of Ultrasound images

Pre-processing for Muscle Motion Analysis: Adaptive Guided I...

引用

Annual International conference of the IEEE Engineering in Medicine and Biology Society

作者： Ye Chen Yongjin Zhou Kamen Ivanov Jizhou Li Yuanzhong Shu Lei Wang The Shenzhen Key Laboratory for Low-cost Healthcare China

ISBN: (纸本)9781457702150

Skeletal muscle is an important tissue of human body, and its contractions control and regulate body motions. Muscle contraction results in morphological changes of the related muscles. Ultrasound imaging is an effective tool for studying muscle architectures and monitoring the morphological changes of muscles. The latter process can be realized with a motion estimation algorithm. However, ultrasound images are usually corrupted by speckle noises and performance of motion estimation methods can be significantly affected by the noises. To get a better performance in motion analysis, in this paper, as a pre-processing step, an adaptive filter named adaptive guided image filtering (AGF) is suggested to reduce speckle noises. We first transformed the multiplicative noise model into an additive one by taking the logarithm of the original speckled data, then performed AGF to obtain the filtered image, and finally took the tackled image back into exponent. Experimental results showed that AGF had a better performance in terms of noise attenuation and edge preservation compared with other standard filters. In quantitative results, the filtered images also had the highest Peak-Signal-to-Noise Ratio (PSNR) using AGF. It's believed that AGF is a good choice for the pre-processing stage of muscle motion analysis.

关键词： Ultrasound image Speckle reduction Adaptive guided image filtering Muscle motion Optical flow

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