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A new descriptor for retrieving 3D objects applied in Congestive Heart Failure diagnosis 29

A new descriptor for retrieving 3D objects applied in Conges...

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29th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Biscaro, Helton H. Oliveira, Hellyan Bergamasco, Leila C. C. Nunes, Fatima L. S. Univ Sao Paulo Lab Comp Applicat HealthCare Sch Arts Sci & Humanities Polytech Sch Sao Paulo Brazil

ISBN: (纸本)9781509035687

Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the object in order to represent it usually as a real number or a vector in Rn. this article presents the Spectral Descriptor, a new descriptor designed for retrieving three-dimensional geometric objects applied to aid the diagnosis of Congestive Heart Failure (CHF). Our descriptor is based on techniques of compressive sensing and rewrites the coordinates of 3D objects vertices on a basis on which they have a sparse representation. Tests with surfaces reconstructed from heart MRI images, specifically from left ventricle, show that the descriptor has presented a good performance, reaching an average precision of approximately 85% for CHF and 71% for non-CHF cases, maintaining high levels of precision. Results also showed that the Spectral Descriptor can decrease the high dimensionality of features vectors in CBIR systems.

关键词： Content-Based image Retrieval (CBIR) Spectral Descriptor three-dimensional Objects Congestive Heart Failure

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Detection of Leukocytes in Intravital Video Microscopy Based on the Analysis of Hessian Matrix Eigenvalues 28

Detection of Leukocytes in Intravital Video Microscopy Based...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Gregorio da Silva, Bruno C. Ferrari, Ricardo J. Carvalho-Tavares, Juliana Univ Fed Sao Carlos Dept Comp Sci Sao Carlos SP Brazil Univ Fed Minas Gerais Dept Physiol & Biophys Belo Horizonte MG Brazil

ISBN: (纸本)9781467379625

Detection of rolling and adhered leukocytes in intravital microscopy image sequences is an important task in studies of leukocyte-endothelial interactions in the microcirculation of living small animals under different inflammatory conditions. this procedure is usually performed by visual assessment of the image sequences. However, despite being tedious and time consuming, this procedure is prone to the inter-and intraobserver variability. In this work, we developed an automated computer system for the detection of leukocytes in intravital video microscopy. First, the video frames were processed by the bilateral filter to reduce noise while preserving sharp edges. then, a demons-based image registration technique was applied to minimize animal motion. Finally, the detection of leukocytes was performed by local analysis of Hessian matrix eigenvalues. Quantitative and qualitative evaluation of the proposed method were conducted by using 220 video frames obtained from an experimental study performed on the brain microvasculature of mice. the proposed method was compared with the template matching technique using precision, recall and F1-Score measures. For the Hessian-based method, the results of precision, recall and F1-Score were, respectively, equal to 0.81, 0.86, and 0.83. For direct comparison, the results obtained for the template matching technique were 0.86, 0.73 and 0.79.

关键词： detection of leukocytes intravital video microscopy temporal image registration

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Reducing the need for bounding box annotations in Object Detection using image Classification data 34

Reducing the need for bounding box annotations in Object Det...

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34th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Blanger, Leonardo Hirata, Nina S. T. Jiang, Xiaoyi Neuralmind AI Campinas SP Brazil Univ Sao Paulo Inst Math & Stat Sao Paulo Brazil Univ Munster Fac Math & Comp Sci Munster Germany

ISBN: (纸本)9781665423540

We address the problem of training Object Detection models using significantly less bounding box annotated images. For that, we take advantage of cheaper and more abundant image classification data. Our proposal consists in automatically generating artificial detection samples, with no need of expensive detection level supervision, using images with classification labels only. We also detail a pretraining initialization strategy for detection architectures using these artificially synthesized samples, before finetuning on real detection data, and experimentally show how this consistently leads to more data efficient models. With the proposed approach, we were able to effectively use only classification data to improve results on the harder and more supervision hungry object detection problem. We achieve results equivalent to those of the full data scenario using only a small fraction of the original detection data for Face, Bird, and Car detection.

关键词： Training graphics Annotations Object detection Birds Data models Proposals

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A Filtering and image Preparation Approach to Enhance OCR for Fiscal Receipts 37

A Filtering and Image Preparation Approach to Enhance OCR fo...

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37th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Auad, Manoela Alves, Sarah Kakizaki, Gabriel Reis, Julio C. S. Silva, Michel M. Univ Fed Vicosa UFV Dept Informat Vicosa MG Brazil

ISBN: (纸本)9798350376043;9798350376036

Photographing fiscal receipts has become increasingly common with the rise of online storage and accounting services. However, capturing images in uncontrolled environments often leads to distortions that can compromise Optical Character Recognition (OCR) techniques, turning the output text unreadable. To address this problem, we propose an expert open-source filtering approach based on low-level features to identify and discard poor-quality fiscal images, select high-quality ones, and flag images that need preparation before OCR. the flagged images undergo a series of enhancement techniques, including homography transformation, super-resolution, noise reduction, sharpness adjustment, morphological operations, and binarization. Our extensive experimental evaluation, executed in a new proposed labeled dataset of fiscal receipt, shows that the proposed method lowers the average Character Error Rate metric by up to 11 points compared to baseline methods. Additionally, an ablation study reveals the impact on the accuracy of each image preparation step.

关键词： Noise abatement

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Proceedings - SIBGRAPI 2006: XIX brazilian symposium on computer graphics and image processing

Proceedings - SIBGRAPI 2006: XIX Brazilian Symposium on Comp...

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SIBGRAPI 2006: 19th brazilian symposium on computer graphics and image processing

ISBN: (纸本)0769526861

the proceedings contain 44 papers. the topics discussed include: dealing with multi-scale depth changes and motion in depth edge detection;parabolic polygons and discrete affine geometry;actively illuminated objects using graph-cuts;a computer-assisted colorization algorithm based on topological difference;increasing statistical power in medical image analysis;non-extensive entropy for CAD systems of breast cancer images;hardware-assisted rendering of CSG models;plausible image based soft shadows using occlusion textures;directing the attention of a wearable camera by pointing gestures;subspace hierarchical particle filter;robust adaptive meshes for implicit surfaces;a statistical discriminant model for face interpretation and reconstruction;vector field reconstruction from sparse samples with applications;motion segmentation using mathematical morphology;detection of unusual motion using computer vision;and video segmentation by supervised learning.

关键词： computer graphics

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Vocal tract morphology using real-time magnetic resonance imaging 30

Vocal tract morphology using real-time magnetic resonance im...

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30th SIBGRAPI Conference on graphics, Patterns and images Tutorials (SIBGRAPI-T)

作者： Sampaio, Rafael de A. Jackowski, Marcel P. Univ Sao Paulo Inst Matemat & Estat Sao Paulo Brazil

ISBN: (纸本)9781538622193

Real-time Magnetic Resonance Imaging (rtMRI) leads to the dynamic observation of hidden processes of articulation in an unprecedented way. the non-invasive image acquisition nature of MRI combined with enhanced anatomical discrimination made rtMRI the reference in capturing vocal tract configurations during speech production. However, this development also unveiled challenges, such as the shape extraction and analysis of the vocal tract contours automatically. this work describes automated techniques for the segmentation of the vocal tract and identification of articulatory structures using rtMRI. the identification of these structures is vital for modeling articulatory synthesis. the methodology is based on level set methods to outline the vocal tract shape. Changes in the vocal tract shape and its structures were investigated for different corpora in order to bind the expression of phonemes and the behavior of the anatomical shapes. these shapes were labeled from basal form invariants, whose final evolution yielded the classification of regions of interest. the methodology resulting from this work may be employed in accent-suppression systems, speech production for laryngectomized patients, and therapetic techniques for children suffering from speech apraxia.

关键词： Shape image segmentation Speech Level set Production Tongue

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Orthogonal Hankel Subspaces for Applications in Gesture Recognition 30

Orthogonal Hankel Subspaces for Applications in Gesture Reco...

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30th SIBGRAPI Conference on graphics, Patterns and images Tutorials (SIBGRAPI-T)

作者： Gatto, Bernardo B. dos Santos, Eulanda M. Waldir, S. S. Junior Univ Fed Amazonas Manaus Amazonas Brazil

ISBN: (纸本)9781538622193

Gesture recognition is an important research area in video analysis and computer vision. Gesture recognition systems include several advantages, such as the interaction with machines without needing additional external devices. Moreover, gesture recognition involves many challenges, as the distribution of a specific gesture largely varies depending on viewpoints due to its multiple joint structures. In this paper, We present a novel framework for gesture recognition. the novelty of the proposed framework lies in three aspects: first, we propose a new gesture representation based on a compact trajectory matrix, which preserves spatial and temporal information. We understand that not all images of a gesture video are useful for the recognition task, therefore it is necessary to create a method where it is possible to detect the images that do not contribute to the recognition task, decreasing the computational cost of the overall framework. Second, we represent this compact trajectory matrix as a subspace, achieving discriminative information, as the trajectory matrices obtained from different gestures generate dissimilar clusters in a low dimension space. Finally, we introduce an automatic procedure to infer the optimal dimension of each gesture subspace. We show that our compact representation presents practical and theoretical advantages, such as compact representation and low computational requirements. We demonstrate the advantages of the proposed method by experimentation employing Cambridge gesture and Human-computer Interaction datasets.

关键词： Gesture recognition Feature extraction Hidden Markov models image recognition Eigenvalues and eigenfunctions Covariance matrices Complexity theory

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Exploiting Convolutional Neural Networks and preprocessing techniques for HEp-2 cell classification in immunofluorescence images 30

Exploiting Convolutional Neural Networks and preprocessing t...

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30th SIBGRAPI Conference on graphics, Patterns and images Tutorials (SIBGRAPI-T)

作者： Rodrigues, Larissa Ferreira Naldi, Murilo Coelho Mari, Joao Fernando UFV Inst Ciencias Exatas & Tecnol Caixa Postal 22 BR-38810000 Rio Paranaiba MG Brazil

ISBN: (纸本)9781538622193

Autoimmune diseases are the third cause of mortality in the world. the identification of anti-nuclear antibody (ANA) via Immunofluorescence (IIF) test in human epithelial type-2 cells (HEp-2) is a conventional method to support the diagnosis of such diseases. In the present work, three popular Convolutional Neural Networks (CNNs) are evaluated for this task: LeNet-5, AlexNet, and GoogLeNet. We also assess the impact of six different pre-processing strategies on the performance of these CNNs. Additionally, data augmentation based on the rotation of the training set images after the pre-processing strategies was evaluated. Our work is the first to consider AlexNet and GoogLeNet models for the proposed analysis and classification of HEp-2 cells images, besides the LeNet-5. Experimental results allow to conclude that neither pre-processing strategies were essential to improve accuracy values of the CNNs. However, when data augmentation is considered, contrast enhancement followed by data centralization is significant in order to achieve good results. Additionally, our results were compared with results from other state-of-art papers. Our best results were achieved by GoogLeNet architecture trained with images with no preprocessing and no data augmentation, resulting in 98.17% of accuracy, which outperforms the results presented in other works in literature.

关键词： Convolutional neural networks HEp-2 cells staining patterns classification LeNet-5 AlexNet GoogLeNet pre-processing data augmentation

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An Approach to Iris Contact Lens Detection based on Deep image Representations 28

An Approach to Iris Contact Lens Detection based on Deep Ima...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Silva, Pedro Luz, Eduardo Baeta, Rafael Menotti, David Pedrini, Helio Falcao, Alexandre Xavier Fed Univ Ouro Preto UFOP Dept Comp BR-35400000 Ouro Preto MG Brazil Univ Campinas UNICAMP Inst Comp BR-13083852 Campinas SP Brazil

ISBN: (纸本)9781467379625

Spoofing detection is a challenging task in biometric systems, when differentiating illegitimate users from genuine ones. Although iris scans are far more inclusive than fingerprints, and also more precise for person authentication, iris recognition systems are vulnerable to spoofing via textured cosmetic contact lenses. Iris spoofing detection is also referred to as liveness detection (binary classification of fake and real images). In this work, we focus on a three-class detection problem: images with textured (colored) contact lenses, soft contact lenses, and no lenses. Our approach uses a convolutional network to build a deep image representation and an additional fully-connected single layer with softmax regression for classification. Experiments are conducted in comparison with a state-of-the-art approach (SOTA) on two public iris image databases for contact lens detection: 2013 Notre Dame and IIIT-Delhi. Our approach can achieve a 30% performance gain over SOTA on the former database (from 80% to 86%) and comparable results on the latter. Since IIIT-Delhi does not provide segmented iris images and, differently from SOTA, our approach does not segment the iris yet, we conclude that these are very promising results.

关键词： Iris Biometrics Contact Lens Detection Deep Learning Convolutional Networks

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DALI:: A methodology for the co-design of dataflow applications on hardware/software architectures 16

DALI:: A methodology for the co-design of dataflow applicati...

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16th symposium on Integrated Circuits and Systems Design

作者： Véstias, MP Neto, HC INESC ID IST Lisbon Portugal

ISBN: (纸本)076952009X

the design of dedicated systems is being subject to severe cost, performance, time-to-market and flexibility constraints. So, it is becoming a quite complex process. this paper proposes a system-level methodology to help in the design of dedicated architectures, possibly with both hardware and software components, for dataflow-dominated applications. the methodology helps the designer to find the best architecture for a particular customer's specification. the potential of the proposed methodology is illustrated with the design of a system for video encoding.

关键词： Application software computer architecture Design methodology Digital signal processing Digital signal processing chips Digital systems Hardware Process design Productivity System-level design

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