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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331-340 订阅

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A NOvEL HYPERSPECTRAL imageS DESTRIPING METHOD BASED ON EDGE RECONSTRUCTION AND ADAPTIvE morphological OPERATORS

A NOVEL HYPERSPECTRAL IMAGES DESTRIPING METHOD BASED ON EDGE...

引用

IEEE International conference on image processing

作者： Yidan Teng Ye Zhang Yushi Chen Chunli Ti School of Electronics and Information Technology Harbin Institute of Technology

ISBN: (纸本)9781479957521

In recent years, the specialized destriping methods for remote-sensing image emphasize efficiency and flexibility but lose the particulars in wide stripes. Though many excellent inpainting algorithms have been proposed, most of them are too complex and inefficient for hyperspectral image (HSI). In this paper, we propose a novel automatic completing method which is appropriate for the feature of HSI and easy to be implemented in parallel. The boundary information in broken region is restored primarily based on SvM with the input of the surrounding detected edges. Then we introduce an adaptive morphological filling operator restrained by the boundaries to estimate the pixels in the same position of all bands synchronously. Experimental results show satisfactory performance of the proposed system and its significance on HSI completion.

关键词： Hyperspectral image Destriping Edge restoring SvM Adaptive morphological operator

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Breast MRI tumour segmentation using modified automatic seeded region growing based on particle swarm optimization image clustering 17

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17th Online World conference on Soft Computing in Industrial Applications, WSC17

作者： Al-Faris, Ali Qusay Ngah, Umi Kalthum Isa, Nor Ashidi Mat Shuaib, Ibrahim Lutfi Universiti Sains Malaysia Penang Malaysia Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9783319009292

In this paper, a segmentation system with a modified automatic Seeded Region Growing (SRG) based on Particle Swarm Optimization (PSO) image clustering will be presented. The paper is focused on Magnetic Resonance Imaging (MRI) breast tumour segmentation. The PSO clusters’ intensities are involved in the proposed algorithms of the automated SRG initial seed and threshold value selection. Prior to that, some pre-processing methodologies are involved. And breast skin is detected and deleted using the integration of two algorithms, i.e. Level Set Active Contour and morphological Thinning. The system is applied and tested on the RIDER breast MRI dataset, and the results are evaluated and presented in comparison to the Ground Truths of the dataset. The results show higher performance compared to the previous segmentation approaches that have been tested on the same dataset. © Springer International Publishing Switzerland 2014.

关键词： Magnetic resonance imaging

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A morphological METHOD FOR MUSIC SCORE STAFF REMOvAL

A MORPHOLOGICAL METHOD FOR MUSIC SCORE STAFF REMOVAL

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IEEE International conference on image processing

作者： Thierry Geraud EPITA Research and Development Laboratory (LRDE) Le Kremlin-Bicêtre France

Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. In this paper we present the method that has won in 2013 the staff removal competition, organized at the International conference on Document Analysis and Recognition (ICDAR). The main characteristics of this method is that it essentially relies on mathematical morphology filtering. So it is simple, fast, and its full source code is provided to favor reproducible research.

关键词： Morphology Text analysis image analysis Robustness image reconstruction image segmentation

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PEDESTRIAN COUNTING BASED ON SPATIAL AND TEMPORAL ANALYSIS

PEDESTRIAN COUNTING BASED ON SPATIAL AND TEMPORAL ANALYSIS

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IEEE International conference on image processing

作者： Zhongjie Yu Chen Gong Jie Yang Li Bai Instn. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781479957521

Pedestrian counting is an important component of video processing. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-temporal matrix, this paper aims to count pedestrians without tracking. As a result, a more robust and efficient pedestrian counting algorithm can be developed. Extensive experiment reveal that our system achieves satisfying performances in terms of both accuracy and efficiency.

关键词： matrix algebra pedestrians support vector machines video surveillance pedestrian counting algorithm spatial-and-temporal analysis spatial-temporal matrix support vector machine video camera video processing visual tracking Bandwidth Cameras Clustering algorithms conferences Feature extraction Real-time systems Support vector machines Mean-shift Clustering Pedestrian Counting Spatial and Temporal Analysis Support vector Machine video Surveillance Support vector Network video monitoring visual tracking Pedestrians Clustering algorithms Cameras real-time systems matrix algebra video cameras Feature extraction Bandwidth

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A framework for automatic detection of lumen-endothelium border in intracoronary OCT image sequences

A framework for automatic detection of lumen-endothelium bor...

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13th Mediterranean conference on Medical and Biological Engineering and Computing 2013, MEDICON 2013

作者： Cheimariotis, G. Koutkias, v. Chouvarda, I. Toutouzas, K. Chatzizisis, Y.S. Giannopoulos, A. Riga, M. Antoniadis, A. Doulaverakis, C. Tsampoulatidis, I. Kompatsiaris, I. Stefanadis, C. Giannoglou, G. Maglaveras, N. Lab of Medical Informatics Medical School Aristotle University Thessaloniki Greece 1st Department of Cardiology Athens Medical School Hippokration Hospital Athens Greece Cardiovascular Engineering and Atherosclerosis Laboratory 1st Cardiology Department AHEPA University Hospital Medical School Aristotle University Thessaloniki Greece Information Technologies Institute Center for Research and Technology-Hellas Thessaloniki Greece

ISBN: (纸本)9783319008455

Intracoronary optical coherence tomography (OCT) is increasingly being used for real-time visualization of coronary arteries aiming to help in the identification of highrisk atherosclerotic plaques associated with geometrical and morphological features of the arterial wall. This paper presents a framework towards the automatic detection of the inner wall of the coronary artery (lumen-endothelium border) in intracoronary OCT image sequences by employing a multistep image processing method. The major focus of this work was to address difficult cases that are frequently met in intracoronary OCT, e.g. images with small/big branches, multiple branches, blood presence, calcifications, artifacts, etc. We present each step employed and the results obtained both in qualitative and quantitative terms. The proposed segmentation algorithm has been proven very efficient in the majority of the examined cases. © Springer International Publishing Switzerland 2014.

关键词： Optical tomography

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ELLIPSES FROM TRIANGLES

ELLIPSES FROM TRIANGLES

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IEEE International conference on image processing

作者： M. Cicconet K. Gunsalus D. Geiger M. Werman Center for Genomics and Systems Biology New York University Courant Institute of Mathematical Sciences New York University

ISBN: (纸本)9781479957521

We present an ellipse finding and fitting algorithm that uses points and tangents, rather than just points, as the basic unit of information. These units are analyzed in a hierarchy: points with tangents are paired into triangles in the first layer and pairs of triangles in the second layer vote for ellipse centers. The remaining parameters are estimated via robust linear algebra: eigen-decomposition and iteratively reweighed least squares. Our method outperforms the state-of-the-art approach in synthetic images and microscopic images of cells.

关键词： Ellipse detection Ellipse fitting Pattern recognition image analysis Cell counting

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RESIDUAL APPROACH ON A HIERARCHICAL SEGMENTATION

RESIDUAL APPROACH ON A HIERARCHICAL SEGMENTATION

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IEEE International conference on image processing

作者： Beatriz Marcotegui MINES ParisTech PSL Research University CMM - Centre for Mathematical Morphology France

Residual operators analyze the evolution of an image subject to the application of a series of transformations, for example a series of openings of increasing size. When a significant object is filtered out by a transformation corresponding to its size, an important residue is observed. Maximal residues are kept for each pixel, indicating the most significant objects present in the image. Different families of operators have been used in the literature: morphological openings or closings, attribute openings or openings by reconstruction. In this paper we propose to compute residues on a hierarchy of partitions, computing the differences between regions at different hierarchical levels based on the classical earth mover's distance. The advantage of our approach is that it is autodual and generic as it can be applied with any hierarchical approach.

关键词： image segmentation Partitioning algorithms Morphology Signal processing algorithms Earth Object segmentation

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Robust Human Detection, Tracking, and Recognition in Crowded Urban Areas

Robust Human Detection, Tracking, and Recognition in Crowded...

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5th conference on Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR as part of the SPIE Defense and Security Sensing Symposium

作者： Chen, Hai-Wen McGurr, Mike Booz Allen Hamilton Inc Belcamp MD 21017 USA

ISBN: (纸本)9781628410167

In this paper, we present algorithms we recently developed to support an automated security surveillance system for very crowded urban areas. In our approach for human detection, the color features are obtained by taking the difference of R, G, B spectrum and converting R, G, B to HSv (Hue, Saturation, value) space. morphological patch filtering and regional minimum and maximum segmentation on the extracted features are applied for target detection. The human tracking process approach includes: 1) Color and intensity feature matching track candidate selection;2) Separate three parallel trackers for color, bright (above mean intensity), and dim (below mean intensity) detections, respectively;3) Adaptive track gate size selection for reducing false tracking probability;and 4) Forward position prediction based on previous moving speed and direction for continuing tracking even when detections are missed from frame to frame. The Human target recognition is improved with a Super-Resolution image Enhancement (SRIE) process. This process can improve target resolution by 3-5 times and can simultaneously process many targets that are tracked. Our approach can project tracks from one camera to another camera with a different perspective viewing angle to obtain additional biometric features from different perspective angles, and to continue tracking the same person from the 2nd camera even though the person moved out of the Field of view (FOv) of the 1st camera with 'Tracking Relay'. Finally, the multiple cameras at different view poses have been geo-rectified to nadir view plane and geo-registered with Google-Earth (or other GIS) to obtain accurate positions (latitude, longitude, and altitude) of the tracked human for pin-point targeting and for a large area total human motion activity top-view. Preliminary tests of our algorithms indicate than high probability of detection can be achieved for both moving and stationary humans. Our algorithms can simultaneously track more tha

关键词： Cameras Target detection image processing Feature extraction image segmentation Biometrics Detection and tracking algorithms Relays Target recognition Automatic tracking

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GENERALIZED-KFCS: MOTION ESTIMATION ENHANCED KALMAN FILTERED COMPRESSIvE SENSING FOR vIDEO

GENERALIZED-KFCS: MOTION ESTIMATION ENHANCED KALMAN FILTERED...

引用

IEEE International conference on image processing

作者： Xin Ding Wei Chen Ian Wassell Computer Laboratory University of Cambridge State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

ISBN: (纸本)9781479957521

In this paper, we propose a Generalized Kalman Filtered Compressive Sensing (Generalized-KFCS) framework to reconstruct a video sequence, which relaxes the assumption of a slowly changing sparsity pattern in Kalman Filtered Compressive Sensing [1, 2, 3, 4]. In the proposed framework, we employ motion estimation to achieve the estimation of the state transition matrix for the Kalman filter, and then reconstruct the video sequence via the Kalman filter in conjunction with compressive sensing. In addition, we propose a novel method to directly apply motion estimation to compressively sensed samples without reconstructing the video sequence. Simulation results demonstrate the superiority of our algorithm for practical video reconstruction.

关键词： Kalman filters compressed sensing data compression image reconstruction image sampling image sequences matrix algebra motion estimation video coding generalized Kalman filtered compressive sensing generalized-KFCS state transition matrix estimation video compression video reconstruction video sampling video sequence Compressed sensing image reconstruction Indexes Motion estimation Sensors video sequences

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RETRIEvAL OF PATHOLOGY image FOR BREAST CANCER USING PLSA MODEL BASED ON TEXTURE AND PATHOLOGICAL FEATURES

RETRIEVAL OF PATHOLOGY IMAGE FOR BREAST CANCER USING PLSA MO...

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IEEE International conference on image processing

作者： Yushan Zheng Zhiguo Jiang Jun Shi Yibing Ma Image Processing Center School of Astronautics Beihang University Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781479957521

Content-based image retrieval (CBIR) for digital pathology slides is of clinical use for breast cancer aided diagnosis. One of the largest challenges in CBIR is feature extraction. In this paper, we propose a novel pathology image retrieval method for breast cancer, which aims to characterize the pathology image content through texture and pathological features and further discover the latent high-level semantics. Specifically, the proposed method utilizes block Gabor features to describe the texture structure, and simultaneously designs nucleus-based pathological features to describe morphological characteristics of nuclei. Based on these two kinds of local feature descriptors, two codebooks are built to learn the probabilistic latent semantic analysis (pLSA) models. Consequently, each image is represented by the topics of pLSA models which can reveal the semantic concepts. Experimental results on the digital pathology image database for breast cancer demonstrate the feasibility and effectiveness of our method.

关键词： image retrieval Feature extraction Computer aided diagnosis Breast cancer Probabilistic latent semantic analysis

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