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检索条件"任意字段=28th SIBGRAPI Conference on Graphics, Patterns and Images SIBGRAPI"

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Segmentation and Removal of Markings in Metal Inspection images

Segmentation and Removal of Markings in Metal Inspection Ima...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Luciane Soares Eduardo Evangelista Vinicius Maurente Matheus M. Dos Santos Igor Maurell Marcelo Pias Paulo Drews Silvia S. C. Botelho Center for Computational Science-C3 Universidade Federal do Rio Grande - FURG Rio Grande Brazil

the inspection process of metallic surfaces, especially FPSO tanks, is still heavily reliant on manual methods, requiring long production downtime and posing health risks to inspectors. Automating this analysis step will provide significant benefits to the management of these vessels' integrity, reducing expenses, downtime, and, most importantly, the exposure time of employees to hazards associated with inspection activities. During manual inspections, inspectors make annotations using paint, typically in white and yellow colors, directly on the tank walls, hindering the automation of the inspection process as it complicates the segmentation and identification of potential flaws on the tank wall using techniques such as neural network models. Recognizing this problem, this work presents a proposal for the identification and segmentation of these markings by segmenting them in the images, followed by the removal of the segmented markings using image texture-filling techniques.

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Structural Analysis of Histological images to Aid Diagnosis of Cervical Cancer

Structural Analysis of Histological Images to Aid Diagnosis ...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Gisele Helena Barboni Miranda Junior Barrera Edson Garcia Soares Joaquim Cezar Felipe Department of Computing and Mathematics Faculty of Philosophy Sciences and Languages of Ribeirão Preto USP Brazil Department of Computer Science Institute of Mathematics and Statistics USP Brazil Department of Pathology Faculty of Medicine of Ribeirão Preto USP Brazil

the use of computational techniques in the processing of histopathological images allows the study of the structural organization of tissues and their pathological changes. the overall objective of this work includes the proposal, the implementation and the evaluation of a methodology for the analysis of cervical intraepithelial neoplasia (CIN) from histopathological images. For this purpose, a pipeline of morphological operators were implemented for the segmentation of cell nuclei and the Delaunay Triangulation were used in order to represent the tissue architecture. Also, clustering algorithms and graph morphology were used to automatically obtain the boundary between the histological layers of the epithelial tissue. Similarity criteria and adjacency relations between the triangles of the network were explored. the proposed method was evaluated concerning the detection of the presence of lesions in the tissue as well as the their malignancy grading.

关键词： Image segmentation Lesions Vectors Cancer Clustering algorithms Image reconstruction Computer architecture

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Information theory-Based Detection of Noisy Bit Planes in Medical images

Information Theory-Based Detection of Noisy Bit Planes in Me...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Hugo N. De Oliveira Jefersson Alex Dos Santos Matheus C. de Melo thaís G. do Rêgo Leonardo V. Batista Universidade Federal de Minas Gerais Belo Horizonte MG BR Centro de Inf. Universidade Federal da Paraiba Joao Pessoa PB BR Centro de Inf. Universidade Federal da Paraíba João Pessoa Brazil

ISBN: (纸本)9781509035694;9781509035687

Mammographic Computer-Aided Diagnosis systems are applications designed to assist radiologists in diagnosis of malignancy in mammographic findings. Most methods described in the literature do not perform a proper preprocessing step in mammographic images prior to classification, which can generate inconsistent results due to the potentially large amount of noise in medical images. this paper proposes a new method based on Information theory and Data Compression for detection of random noise in image bit planes. In order to validate the efficiency of the proposed noise removal method, we used Machine Learning algorithms to classify mammographic findings from the Digital Database for Screening Mammography. Results using texture features indicate that a reduction in the radiometric resolution of 4 or 5 bit planes in digitized screen film mammographic images result in a better classification performance.

关键词： Breast cancer Mammography Delta-sigma modulation Entropy Noise measurement Context

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Enhancing the Visualization of the Microvasculature of Extrahepatic Bile Ducts Obtained from Confocal Microscopy images

Enhancing the Visualization of the Microvasculature of Extra...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Lizeth A. C. Beltran Jorge Luiz dos Santos Carolina Uribe Cruzz Carla M. D. S. Freitas Institute of Informatics Federal University of Rio Grande do Sul UFRGS Porto Alegre Brazil Universidade da Beira Interior Covilha Castelo Branco PT Lab. Exp. de Hepatologia e Gastroenterologia Porto Alegre Brazil

ISBN: (纸本)9781509035694;9781509035687

Confocal microscopy is an important tool for visualizing 3D datasets of fluorescent specimens, and has been used to investigate the structure of biological specimens. However, such images are affected by the noise introduced during the specimen preparation and image acquisition processes. Anisotropic diffusion is a non-linear filter that can significantly improve image quality while removing noise without blurring edges. this study investigates the application of anisotropic diffusion in confocal microscopy images by exploring different models for parameters' calculation. Our data consists of several slices of extrahepatic bile ducts containing a network of small vessels named Peribiliary Vascular Plexus (PVP), which are affected by several sources of noise. Experimental results show that anisotropic diffusion improved the volumetric visualization of the PVP. We validated the results using MSE and PSNR quantitative approaches and qualitative description by an expert user.

关键词： Microscopy Ducts Anisotropic magnetoresistance Mathematical model Estimation Mice three-dimensional displays

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Contextual Filtering of CT images Using Markovian Wiener Filters with a Non Local Means Approach for Statistical Estimation

Contextual Filtering of CT Images Using Markovian Wiener Fil...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Denis H. P. Salvadeo Nelson D. A. Mascarenhas Alexandre L. M. Levada Computer Department Federal University of São Carlos Sao Carlos Brazil

Recently, investigations on medical imaging have been indicating a strong correlation between cases of cancers and the increasing number of Computed Tomography (CT) exams, mainly due to high radiation doses to which patients are exposed during the data acquisition process. thus, there is a need to reduce the radiation doses whereas still keeping satisfactory quality images for diagnosis. In this paper, we propose to filter noise in CT images using contextual versions of Wiener Filter such as Generalized Wiener Filter (GWF) and Non Local Means approach for parameter estimation. Experiments show that the proposed methods are promising, since they provide good results with no significant increase in the computational cost.

关键词： Wiener filters Computed tomography Phantoms Image reconstruction Noise Noise measurement

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Fast QR Code Detection in Arbitrarily Acquired images

Fast QR Code Detection in Arbitrarily Acquired Images

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Luiz Belussi Nina Hirata Department of Computer Science Institute of Mathematics and Statistics University of Säo Paulo Sao Paulo Brazil

the detection of QR codes, a type of 2D barcode, as described in the literature consists merely in the determination of the boundaries of the symbol region in images obtained with the specific intent of highlighting the symbol. However, many important applications such as those related with accessibility technologies or robotics, depends on first detecting the presence of a barcode in an environment. We employ Viola-Jones rapid object detection framework to address the problem of finding QR codes in arbitrarily acquired images. this framework provides an efficient way to focus the detection process in promising regions of the image and a very fast feature calculation approach for pattern classification. An extensive study of variations in the parameters of the framework for detecting finder patterns, present in three corners of every QR code, was carried out. Detection accuracy superior to 90%, with controlled number of false positives, is achieved. We also propose a post-processing algorithm that aggregates the results of the first step and decides if the detected finder patterns are part of QR code symbols. this two-step processing is done in real time.

关键词： Training Prototypes Boosting Object detection Feature extraction Face detection Decoding

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Memory-Efficient Computation of Persistent Homology for 3D images Using Discrete Morse theory

Memory-Efficient Computation of Persistent Homology for 3D I...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： David Gunther Jan Reininghaus Ingrid Hotz Hubert Wagner Zuse Institute Berlin Berlin Germany Institute of Computer Science Jagiellonian University Krakow Poland

We propose a memory-efficient method that computes persistent homology for 3D gray-scale images. the basic idea is to compute the persistence of the induced Morse-Smale complex. Since in practice this complex is much smaller than the input data, significantly less memory is required for the subsequent computations. We propose a novel algorithm that efficiently extracts the Morse-Smale complex based on algorithms from discrete Morse theory. the proposed algorithm is thereby optimal with a computational complexity of O(n2). the persistence is then computed using the Morse-Smale complex by applying an existing algorithm with a good practical running time. We demonstrate that our method allows for the computation of persistent homology for large data on commodity hardware.

关键词： three dimensional displays Indexes Algorithm design and analysis Computational complexity Feature extraction Memory management

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Analysis of the Eyes on Face images for Compliance with ISO/ICAO Requirements

Analysis of the Eyes on Face Images for Compliance with ISO/...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Erick V. C. L. Borges Igor L. P. Andrezza José R. T. Marques Rajiv A. T. Mota João Janduy B. Primo VSoft Tecnologia João Pessoa PB Brasil Centro de Informática CI Universidade Federal de Campina Grande-UFCG Campina Grande PB Brasil

the face has been used in identity documents and represents the ideal biometric characteristic in many applications. the International Civil Aviation Organization endorsed the use of face as the globally interoperable biometric characteristic. Successively, the International Standard Organization proposed the ISO/IEC 19794-5 standard for face usage in travel documents. the purpose of this work is to evaluate the quality of face images for identification documents and check if the face images satisfy the requirements defined by the ISO/IEC 19794-5. this work presents approaches for the evaluation of the following ISO/ICAO requirements: eyes state, red eyes and looking away. In addition, an approach to estimate the location of the center of the eyes is proposed. the proposed methods to check ISO/ICAO requirements were evaluated using the BioLab-ICAO Framework. the results achieved by the proposed methods were satisfactory, overcoming almost all the works in the literature for this purpose.

关键词： Face Iris Image color analysis Databases Image edge detection Skin Standards

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A Deep Learning Approach for Classification of Reaching Targets from EEG images

A Deep Learning Approach for Classification of Reaching Targ...

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Schubert R. Carvalho Iraquitan Cordeiro Filho Damares Oliveira De Resende Ana Carolina Siravenha Cleidson R.B. De Souza Henrique Debarba Bruno D. Gomes Ronan Boulic Laboratório de Computação Aplicada Instituto Tecnológico Vale (iTV) Brazil Laboratorio de Computacao Aplicada Instituto Tecnologico Vale (ITV) Brazil Instituto de Ciências Biológicas Universidade Federal do Pará (UFPA) Brazil Immersive Interaction Group (IIG) École poly technique fédérale de Lausanne (EPFL) Switzerland Artanim Foundation Switzerland

In this paper, we propose a new approach for the classification of reaching targets before movement onset, during visually-guided reaching in 3D space. Our approach combines the discriminant power of two-dimensional Electroencephalography (EEG) signals (i.e., EEG images) built from short epochs, with the feature extraction and classification capabilities of deep learning (DL) techniques, such as the Convolutional Neural Networks (CNN). In this work, reaching motions are performed into four directions: left, right, up and down. To allow more natural reaching movements, we explore the use of Virtual Reality (VR) to build an experimental setup that allows the subject to perform self-paced reaching in 3D space while standing. Our results reported an increase both in classification performance and early detection in the majority of our experiments. To our knowledge this is the first time that EEG images and CNN are combined for the classification of reaching targets before movement onset.

关键词： Electroencephalography three-dimensional displays Machine learning Training Neural networks Convolution

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Image Micro-pattern Analysis Using Fuzzy Numbers

Image Micro-pattern Analysis Using Fuzzy Numbers

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Brazilian Symposium on Computer graphics and Image Processing (sibgrapi)

作者： Raissa T. Vieira Carlos Eduardo de Oliveira Chierici Carolina T. Ferraz Adilson Gonzaga Department of Electrical Engineering University of São Paulo São Paulo Brazil Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR

this paper proposes a new methodology for micro pattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial context of the image, such as edge, line, spot, blob, corner, texture, and more complex patterns. By treating a pixel neighborhood as a fuzzy set and each pixel gray-level as a fuzzy number, we can evaluate the membership degree of the central pixel to the others. We have called this method the Local Fuzzy Pattern (LFP). Using a sigmoid membership function, we proved that the proposed methodology surpasses the Hit-rate of the Local Binary Pattern (LBP), for texture classification. the LFP proved to be robust to image rotation. Moreover, our proposed formulation for the LFP is a generalization of previously published techniques, such as Texture Unit, LBP, FUNED, and Census Transform.

关键词： Feature extraction Histograms Databases Digital images Fuzzy logic Context Image edge detection

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