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Handwriting Synthesis from Public Fonts 30

Handwriting Synthesis from Public Fonts

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

作者： Balreira, Dennis G. Walter, M. Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781538622193

Handwriting synthesis generates renderings of text which look like they were written by a human but are in fact synthesized by a model. From an input sample of the desired handwriting, we introduce an algorithm that finds the best match between characters using as source for the output text the large collection of publicly available fonts designed to look like handwriting. For each character in the desired output text, we find the best match among the public fonts using a metric that matches both the shape and appearance of the input real character. Once we have the set of best characters we build the output sentence or paragraph by concatenation of individual characters. Our results show that even though human calligraphy is highly individual and specialized, visually similar renderings are possible for many applications that do not demand full similarity. On a user study with 12 subjects, our synthesis results were considered, on average, 71% similar to the input samples.

关键词： Shape CAPTCHAs Writing Rendering (computer graphics) Handwriting recognition Portals Skeleton

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A Comparative Evaluation of Transformer-Based Vision Encoder-Decoder Models for brazilian Portuguese image Captioning 37

A Comparative Evaluation of Transformer-Based Vision Encoder...

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

作者： Bromonschenkel, Gabriel Oliveira, Hilark Paixao, thiago M. Inst Fed Espirito Santo IFES Programa Posgrad Comp Aplicada PPComp Serra Brazil

ISBN: (纸本)9798350376043;9798350376036

image captioning refers to the process of creating a natural language description for one or more images. this task has several practical applications, from aiding in medical diagnoses through image descriptions to promoting social inclusion by providing visual context to people with impairments. Despite recent progress, especially in English, low-resource languages like brazilian Portuguese face a shortage of datasets, models, and studies. this work seeks to contribute to this context by fine-tuning and investigating the performance of vision language models based on the Transformer architecture in brazilian Portuguese. We leverage pre-trained vision model checkpoints (ViT, Swin, and DeiT) and neural language models (BERTimbau, DistilBERTimbau, and GPorTuguese-2). Several experiments were carried out to compare the efficiency of different model combinations using the #PraCegoVer-63K, a native Portuguese dataset, and a translated version of the Flickr30K dataset. the experimental results demonstrated that configurations using the Swin, DistilBERTimbau, and GPorTuguese-2 models generally achieved the best outcomes. Furthermore, the #PraCegoVer-63K dataset presents a series of challenges, such as descriptions made up of multiple sentences and the presence of proper names of places and people, which significantly decrease the performance of the investigated models.

关键词： Visual languages

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Text/non-text classification of connected components in document images 30

Text/non-text classification of connected components in docu...

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

作者： Julca-Aguilar, Frank D. Maia, Ana L. L. M. Hirata, Nina S. T. Univ Sao Paulo Inst Math & Stat Dept Comp Sci Sao Paulo Brazil State Univ Feira de Santana UEFS Dept Exact Sci Feira De Santana Brazil

ISBN: (纸本)9781538622193

Text segmentation is an important problem in document analysis related applications. We address the problem of classifying connected components of a document image as text or non-text. Inspired from previous works in the literature, besides common size and shape related features extracted from the components, we also consider component images, without and with context information, as inputs of the classifiers. Multi-layer perceptrons and convolutional neural networks are used to classify the components. High precision and recall is obtained with respect to both text and non-text components.

关键词： Feature extraction Training image segmentation Shape Data mining Neural networks Layout

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image-based texture analysis for realistic image synthesis 13

Image-based texture analysis for realistic image synthesis

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13th brazilian symposium on computer graphics and image processing, SIBGRAPI 2000

作者： Mayer, Heinz Computer Graphics Vision Graz University of Technology Inffeldgasse 16/II GrazA-8010 Austria

ISBN: (纸本)0769508782

We present a method to measure reflectance and texture of surfaces in a one step process. For later use in digital image synthesis it is mandatory to separate the gathered intensity values into these two parts to eliminate highlighting artifacts from textures. Our image-based measurement system delivers bidirectional reflectance distribution function (BRDF) values distributed over the surface of the material under investigation. After fitting a reflectance model to the gathered data we estimate the modulation of the diffuse reflectance coefficient which represents the texture. the last step analyzes the texture to get a parameterized and compact description of the measured surface properties. these results allow us to apply the gathered surface properties to objects with arbitrary shape and size. To keep the measurement system simple a standard CCD camera and light source are used. © 2000 IEEE.

关键词： Reflection

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Using 3D Texture and Margin Sharpness Features on Classification of Small Pulmonary Nodules 29

Using 3D Texture and Margin Sharpness Features on Classifica...

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

作者： Felix, Ailton Oliveira, Marcelo Machado, Aydano Raniery, Jose Fed Univ Alagoas UFAL IC Maceio Alagoas Brazil Univ Sao Paulo Ribeirao Preto Med Sch FMRP Sao Paulo Brazil

ISBN: (纸本)9781509035687

the lung cancer is the reason of a lot of deaths on population around the world. An early diagnosis brings a most curable and simpler treatment options. Due to complexity diagnosis of small pulmonary nodules, computer-Aided Diagnosis (CAD) tools provides an assistance to radiologist aiming the improvement in the diagnosis. Extracting relevant image features is of great importance for these tools. In this work we extracted 3D Texture Features (TF) and 3D Margin Sharpness Features (MSF) from the Lung image Database Consortium (LIDC) in order to create a classification model to classify small pulmonary nodules with diameters between 3-10mm. We used three machine learning algorithm: k-Nearest Neighbor (k-NN), Multilayer Perceptron (MLP) and Random Forest (RF). these algorithms were trained by different set of features from the TF and MSF. the classification model with MLP algorithm using the selected features from the integration of TF and MSF achieved the best AUC of 0.820.

关键词： lung cancer small nodules early diagnosis computer-aided diagnosis texture features margin sharpness features classification machine learning

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Domain Adaptation for Holistic Skin Detection 34

Domain Adaptation for Holistic Skin Detection

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

作者： Dourado, Aloisio Guth, Frederico de Campos, Teofilo Li Weigang Univ Brasilia UnB Dept Ciencia Comp CIC Brasilia DF Brazil

ISBN: (纸本)9781665423540

Human skin detection in images is a widely studied topic of computer Vision for which it is commonly accepted that analysis of pixel color or local patches may suffice. However, we found that the lack of contextual information may hinder the performance of local approaches. In this paper, we present a comprehensive evaluation of holistic and local Convolutional Neural Network (CNN) approaches on in-domain and cross-domain experiments and compare them with state-of-the-art pixel-based approaches. We also propose combining inductive transfer learning and unsupervised domain adaptation methods evaluated on different domains under several amounts of labelled data availability. We show a clear superiority of CNN over pixel-based approaches even without labeled training samples on the target domain and provide experimental support for the superiority of holistic over local approaches for human skin detection.

关键词： Training graphics computer vision image color analysis Transfer learning Skin Convolutional neural networks

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Breaking Visual Similarity Barriers: Enhanced image Identification through Global-Local Feature Fusion 37

Breaking Visual Similarity Barriers: Enhanced Image Identifi...

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

作者： Oliveira dos Santos, Wagner Luiz Montenegro, Anselmo Antunes Fed Fluminense Univ Dept Comp Sci BR-24210380 Niteroi RJ Brazil

ISBN: (纸本)9798350376043;9798350376036

Effectively distinguishing between images in high visual similarity datasets poses significant challenges, especially with photometric variations, perspective transformations, and/or occlusions. We introduce a novel methodology that fuses local and global feature detection techniques. By integrating local feature analysis with global feature representation based on graph structuring and processing, our approach can capture topological and metric relationships among descriptors. the proposed graph representation is computed using only matching features, hence filtering irrelevant information and focusing on unique image attributes that favor identification. this study aims to answer how the synergistic combination of these techniques can outperform conventional identification methods dealing with data sets with high visual similarity. We performed experiments showing significant improvements in precision and recall, reflected in the F1-Score, of the proposed strategy over pure local-based image identification. the results highlight the potential of hybrid approaches for better image recognition, also revealing that local-based method can use our proposal as an additional component for obtaining improved results.

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On the Performance of Visual Semantics for Improving Texture-based Blind image Quality Assessment 30

On the Performance of Visual Semantics for Improving Texture...

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

作者： Freitas, Pedro Garcia Farias, Mylene C. Q. Univ Brasilia Dept Comp Sci Brasilia DF Brazil Univ Brasilia Dept Elect Engn Brasilia DF Brazil

ISBN: (纸本)9781538622193

Blind image quality assessment (BIQA) methods aim to estimate the quality of a given test image without referring to the corresponding reference (original) image. Most BIQA methods use visual sensitivity models, which take into consideration intrinsic image characteristics (e.g. contrast, luminance, and texture) to identify degradations and estimate quality. For example, texture-based BIQA methods are based on the assumption that visual impairments (degradations) alter the characteristics of the image textures and, therefore, their statistics. Although these methods have been are known to provide an acceptable performance, they do not take into account the semantic information of the image. In this paper, we propose a BIQA method that estimates quality using texture characteristics and semantic information. the texture characteristics are obtained using the Opponent Color Local Binary Pattern (OCL) operator. the semantic information is obtained by estimating the probability distribution of the scene characteristics. A random forest regression algorithm is used to map semantic and texture-based features into a quality score. Results obtained testing the proposed BIQA method on several public databases show the method has a good accuracy on quality prediction.

关键词： Semantics Visualization image color analysis image quality Testing Integrated circuits Training

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Tie-zone watershed, bottlenecks and segmentation robustness analysis

Tie-zone watershed, bottlenecks and segmentation robustness ...

引用

18th brazilian symposium on computer graphics and image processing (SIBGRAPI 2005)

作者： Audigier, R de Alencar Lotufo, R Univ Estadual Campinas Sch Elect & Comp Engn Dept Comp Engn & Ind Automat BR-13083852 Campinas SP Brazil

ISBN: (纸本)0769523897

In a recent paper [1], a new type of watershed (WS) transfbrm was introduced: the tie-zone watershed (TZWS). this region-based watershed transform does not depend on arbitrary implementation and provides a unique (and thereby unbiased) optimal solution. Indeed, many optimal solutions are sometimes possible when segmenting an image by VVS. the TZWS assigns each pixel to a catchment basin (CB) if in all solutions it belongs to this CB. Otherwise, the pixel is said to belong to a tie-zone (TZ). An efficient algorithm computing the TZWS and based on the image Foresting Transform (IFT) was also proposed. In this article, we define the new concept of "bottle-necks" in the watermerging paradigm. Intuitively, the bottlenecks are the first contact points between at least two different wave fronts. the), are pixels in the image where different colored waters meet and tie and from which may begin, therefore, the tie-zones. they represent the origin points or the access of the tie-zones (regions that cannot be labeled without making arbitrary choices). If they are preferentially assigned to one or another colored water according to an arbitrary processing order as occurs in most of watershed algorithm, art entire region (its influence zone -the "bottle"!) is conquered together the bottlenecks play therefore an important role in the bias that could be introduced by a WS implementation. It is why we show in this paper that both tie-zones and bottlenecks analysis can be associated with the robustness of a segmentation.

关键词： image segmentation

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Gravity Alignment for Single Panorama Depth Inference 34

Gravity Alignment for Single Panorama Depth Inference

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

作者： Bergmann, Matheus A. Pinto, Paulo G. L. da Silveira, thiago L. T. Jung, Claudio R. Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781665423540

Monocular depth inference methods based on 360 degrees images allow 3D reconstruction of entire rooms with a single capture. However, most state-of-the-art approaches assume gravity-aligned images and are highly sensitive to camera rotations. Such limitations result in poor depth estimates, which may jeopardize further 3D-based applications. Here, we present a pipeline for spherical single-image depth inference supplied by a novel rotation correction module. We show that our gravity alignment module can improve existing single-image depth estimation methods, being also useful for aligning color and depth to the horizon, which is highly desirable in many applications.

关键词： graphics three-dimensional displays image color analysis Pipelines Estimation Cameras Gravity

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