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Annual IEEE Symposium on computer-Based Medical Systems

作者： Marcelo Dornbusch Lopes Antonio C. Sobieranski Aldo Von Wangenheim Eros Comunello INCoD - National Brazilian Institute for Digital Convergence / LAPIX - Image Processing and Computer Graphics Lab - Federal University of Santa Catarina Brazil Postgraduate Program in Applied Computing University of Itajai Valley - UNIVALI INCoD (Nat. Brazilian Inst. for Digital Convergence) LAPIX (Image Process. & Comput. Graphics Lab.) Universidade Federal de Santa Catarina Florianopolis SC BR

ISBN: (纸本)9781467390378

Histopathological staining is a technique widely used to highlight biological states or pharmacological activities in uman tissue. A quantitative analysis of the resulting images can produce biomarkers for diseases or even other specific conditions, thus providing valuable information for diagnosis and prognosis. Since biomarkers require measurements to be made in an objective and consistent way, software systems are employed to provide this quantitative analysis. For measurements to be reproducible, the same methods must be available across different laboratories. In this paper, we present a tool that allows users to perform quantitative analyses over the web, thus providing an efficient environment not only for individual cases to be evaluated, but also for users to share a common ground when making measurements. The classification method used by the tool to segment stained pixels is performed by a similarity function based on the polynomial version of the Mahalanobis distance, which is nonlinear and provides very robust classification for m-dimensional feature spaces. Furthermore, the similarity function can be generalized in the tool, so that images can be classified by reusing parameters of previous cases. The results of our web-based approach were compared with established ground-truth data sets, producing sensitivity, specificity and fitness values of 97.09%, 98.70%, and 97.90%.

关键词： image color analysis image segmentation Biomarkers Sensitivity Inspection Servers Statistical analysis

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Suspicious face detection based on key frame recognition under surveillance video

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9712 LNCS卷 645-652页

作者： Zheng, Xiaohui Ning, Yi Chen, Xianjun Zhan, Yongsong Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9783319409993

Surveillance video is characterized by large amount of data and redundancy, which makes the suspicious face detection to be a problem. To solve the problem above we proposed suspicious face detection based on key frame. Surveillance video has the type of fixed background, so this paper used the frame difference method with low computational complexity and small computation to extract the key frame. We proposed a new method combined DPM with skin color detection to detect the suspicious face in the key frames. To solve the speed bottleneck of the traditional DPM, we proposed to use the fast HOG LUT feature extraction and the near optimal cost sensitive decision making improving the traditional method. Meanwhile we used YCrCb + otsu skin color segmentation. Since the otsu is easily affected by the illumination, we proposed an improved skin color detection. Experiment results show that the proposed algorithms are robust and accurate for real-time. © Springer International Publishing Switzerland 2016.

关键词： Face recognition

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Optimal surface normal from affine transformation 10

Optimal surface normal from affine transformation

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10th International Conference on computer Vision Theory and Applications, VISAPP 2015

作者： Daniel, Barath Molnar, Jozsef Hajder, Levente Geometric Modelling and Computer Vision Laboratory MTA SZTAKI Kende utca 13-17 BudapestH-1111 Hungary Department of Image Processing and Computer Graphics Institute of Informatics University of Szeged Árpád tér 2 SzegedH-6720 Hungary

ISBN: (纸本)9789897580918

This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that describes the relationship of surface normals, camera projections, and affine transformations. This formula is general since it works for every kind of cameras. We propose novel methods for estimating the normal of a surface patch if the affine transformation is known between two perspective images. We show here that the normal vector can be optimally estimated if the projective depth of the patch is known. Other non-optimal methods are also introduced for the problem. The proposed methods are tested both on synthesized data and images of real-world 3D objects.

关键词： Cameras

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On the optimization of tolerance synthesis with an ontology-based approach

On the optimization of tolerance synthesis with an ontology-...

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Chinese Automation Congress (CAC)

作者： Hongcheng Lu Meifa Huang Yanru Zhong Congwen Zheng Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin PR China

ISBN: (纸本)9781467371902

In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly exchange tolerance information among heterogeneous CAD system. On the optimization of tolerance synthesis with an ontology-based approach is proposed, automatically generated the tolerance type, variations of tolerance, cost function and tolerance value. Firstly, ontology contains abundant semantic knowledge and semantic structure. Secondly, the Web Ontology Language (OWL) is used to define the concepts of tolerance synthesis, and Semantic Web Rule Language (SWRL) is used to define the constraint conditions and distribute experience. Thirdly, based on the genetic algorithm, a tolerance values optimization model is established with manufacturing cost functions and assembly stack-up constraint. Finally, the effectiveness of the proposed approach is illustrated by using a practical example of the gear case.

关键词： Assembly Cost function Feature extraction Ontologies Solid modeling

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Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution

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Light(Science & Applications) 2015年第1期4卷 152-162页

作者： Antonio C Sobieranski Fatih Inci H Cumhur Tekin Mehmet Yuksekkaya Eros Comunello Daniel Cobra Aldo von Wangenheim Utkan Demirci Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Division of Biomedical EngineeringDivision of Renal MedicineDepartment of MedicineBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Division of Infectious DiseasesBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA INCoD–National Brazilian Institute for Digital Convergence/LAPIX Image Processing and Computer Graphics LabFederal University of Santa CatarinaBrazil Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Stanford University School of MedicineCanary Center at Stanford for Cancer Early DetectionPalo AltoCAUSA Present Address:Department of Biomedical Engineering Faculty of Engineering Bas¸kent UniversityAnkaraTurkey VisionLab Master in Applied ComputingUniversity of Itajaı´ValleyBrazil CERTI Foundation FlorianopolisBrazil

In this paper,an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame *** samples are illuminated by a nearly coherent illumination system,where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging *** increase the resolution,a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene,with small planar *** are resolved by a hybrid approach:(i)alignment of the LR images by a fast feature-based registration method,and(ii)fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum *** method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed *** presented approach was evaluated with various biological samples including sperm and platelets,whose dimensions are in the order of a few *** obtained results demonstrate a spatial resolution of 1.55 μm on a field-of-view of<30 mm^(2).

关键词： digital in-line holography image registration lensless imaging point-of-care platform pixel super-resolution

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Portrait image segmentation based on improved grabcut algorithm 6th

Portrait image segmentation based on improved grabcut algori...

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6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Li, Shuai Zheng, Xiaohui Chen, Xianjun Zhan, Yongsong Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin Guangxi541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin Guangxi541004 China Information Engineering School Haikou College of Economics Haikou Hainan571127

ISBN: (纸本)9783319204680

Traditional computer portrait caricature system mainly take the method that exaggerate and deform real images directly, that lead the facial image background also been deformed when exaggerate facial image. If in pretreatment stage, we segmented the characters and background of the input image, and then do the subsequent processing, the problem may be solved. But for better portrait caricature effects, we need an excellent segmentation algorithm. So, we propose an improved Grabcut image segmentation algorithm and use it to extract the prospect character image for exaggeration and deformation. In practical application, we separate deform and exaggerate the foreground characters image with TPS method, then fuse it with the original or new background picture, get the final image. Application proves, the method solves the background deformation problem well, and improves the quality and rate of image segmentation, caricature synthesis effect reality and natural. © Springer International Publishing Switzerland 2015.

关键词： image segmentation

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A fast gabor filter approach for multi-channel texture feature discrimination 19

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19th Iberoamerican Congress on Pattern Recognition, CIARP 2014

作者： Sobieranski, Antonio Carlos Linhares, Rodrigo T. F. Comunello, Eros von Wangenheim, Aldo Federal University of Santa Catarina Laboratory of Image Processing and Computer Graphics Brazil Federal University of Parana Department of Informatics Brazil

ISBN: (纸本)9783319125671

Texture is a very important concept for many image understanding and pattern classification applications. The analysis of texture can be performed by the multi-channel filtering theory, a classical theory for texture perception based on the early stages of human visual system. This approach decomposes an image into a set of responses given by a bank of Gabor filters, that nearly covers in an uniformly manner the spatial-frequency domain. This approach relies on the image dimensions, and the number of kernels in a bank of Gabor filters varies according to the number of combinations between frequencies and orientations. In many practical applications, this large number of combinations makes quickly unfeasible the computation of the whole bank of filters. To ease this problem, in this paper we propose a multi-channel filtering where the Gabor bank for texture discrimination is computed in parallel in a graphics processing unit (GPU). Experimental results show an improvement of 8.78 times for feature extraction when compared against the corresponding CPU-based approach. © Springer International Publishing Switzerland 2014.

关键词： Gabor filters

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Real-Time Fine-Tuned Adjustment of Fiber Tracking Parameters

Real-Time Fine-Tuned Adjustment of Fiber Tracking Parameters

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Adiel Mittmann Eros Comunello Aldo von Wangenheim Image Processing and Computer Graphics Lab-LAPIX Federal University of Santa Catarina-UFSC Florianopolis SC Brazil

Fiber tracking is a mature technique that aids neurosurgeons by providing the location of neuronal fibers in a patient's brain. Although the interactivity of tools have been typically limited, the exploitation of the parallel nature of fiber tracking is rapidly changing this landscape. The parallel environment offered by GPUs and modern CPUs enables fiber tracking to be executed very quickly on consumer-grade computers. The adjustment of fiber tracking parameters can currently be made on the fly, and the new results can be both computed and displayed in real-time on the screen. In order to further improve the interactivity of fiber tracking tools, this article proposes the application of histogram equalization, a traditional digital image processing procedure, to the fiber tracking parameters. The non-linear scale obtained by this process allows the user to interactively explore sensitive regions of the parameter space. Results show that this scale can be computed in real-time and that it can be cleanly integrated into fiber tracking tools.

关键词： Histograms Trajectory Indexes Visualization graphics processing units Real-time systems Anisotropic magnetoresistance

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Color skin segmentation based on non-linear distance metrics 19

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19th Iberoamerican Congress on Pattern Recognition, CIARP 2014

作者： Sobieranski, Antonio Carlos Chiarella, Vito F. Barreto-Alexandre, Eduardo Linhares, Rodrigo T. F. Comunello, Eros von Wangenheim, Aldo Federal University of Santa Catarina Laboratory of Image Processing and Computer Graphics Brazil Federal University of Parana Department of Informatics Brazil University of Sao Paulo Department of Computer Science Brazil

ISBN: (纸本)9783319125671

In this paper we present a semiautomatic method for skin identification in video sequences. The user trains the system by selecting in a frame some typical positive skin pixels, that will be used as a reference for the construction of a nonlinear distance metric. In this learning process the global optimum is obtained by induction employing higher polynomial terms of the Mahalanobis distance, extracting nonlinear features of the skin pattern distributions. These nonlinear features are then used to classify the frames captured from the camera, identifying all skin and non-skin regions on the scene. We adopt an estrategy which enables this method to run in real-time after some iteractions. We also compare our classification method against vector norm (L2) and Mahalanobis distance, showing a better classification for the skin patterns. © Springer International Publishing Switzerland 2014.

关键词： Artificial intelligence

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A fast pavement location approach for autonomous car navigation 19

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19th Iberoamerican Congress on Pattern Recognition, CIARP 2014

作者： Rateke, Thiago Justen, Karla A. Chiarella, Vito F. Linhares, Rodrigo T. F. Sobieranski, Antonio Carlos Comunello, Eros von Wangenheim, Aldo Federal University of Santa Catarina Brazil Laboratory of Image Processing and Computer Graphics National Brazilian Institute for Digital Convergence Brazil Federal University of Parana Department of Informatics Brazil

ISBN: (纸本)9783319125671

This paper describes a fast image segmentation approach designed for pavement detection in a moving camera. The method is based on a graph-oriented segmentation approach where gradient information is used temporally as a system of discontinuities to control merging between adjacent regions. The method presumes that the navigable path usually is located at specific positions on the scene, and a predefined set of seed points is used to locate the region of interest. The obtained results shown the proposed approach is able to accurately detect in an inexpensive computation manner the navigable path even in non-optimum scenarios such as miss-painted or unpaved dirt roads. Validation was conducted using a dataset with 701 samples of navigable paths, presenting a very high precision for real-time applications. © Springer International Publishing Switzerland 2014.

关键词： Pavements

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