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An Efficient Method for Porosity Properties Extraction of Carbonate Rocks

An Efficient Method for Porosity Properties Extraction of Ca...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Victor G. Cardoso Edna N. S. Barros José A. Barbosa Antonio D. Antonino Abraão V. Nova Center of Informatics Federal University of Pernambuco Recife Pernambuco Brazil Federal University of Pernambuco Recife Pernambuco Brazil

ISBN: (数字)9781728192741

ISBN: (纸本)9781728192758

Porous media characterization presents substantial importance for the oil industry. The X-ray micro-computed tomography (μCT) is often used to generate digital models of reservoir rocks. This paper presents an automatic histogram-based method for the segmentation of μ CT images, which allows the fast extraction of some petrophysical properties. The processing is based on the analysis of the typical 2D images used to produce 3D volumes. The method was applied to analyze seven samples of carbonate rocks, to define the porosity values, pores size distribution, and the orientation of the pores. Calculated porosity values were compared to the porosity results obtained with a helium porosimeter. The comparison of porosity calculated by this method against the experimental values showed an average error of 3.43%. The computational time spent for each sample processing was of about 9 minutes on a regular PC. The method can be used to extract porosity parameters in a large number of samples with a substantial gain of time and computational power.

关键词： Rocks Computed tomography image segmentation Histograms Data mining Two dimensional displays Three-dimensional displays

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Wild boar Classification by Using a Fusion of Texture Analysis Methods

Wild boar Classification by Using a Fusion of Texture Analys...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Luís C. S. Júnior Maricéia B. S. Pàdua Leonardo M. Ogusuku Marcelo K. Albertini Renato Pimentel André R. Backes School of Computer Science Federal University of Uberlandia Av. João Naves de Ávila 2121 Uberlandia MG Brazil Triangle Regional Unit State Forest Institute MG Brazil

ISBN: (数字)9781728192741

ISBN: (纸本)9781728192758

In several countries the wild boar is an invasive species that remains widespread mainly due its adaptability and uncontrolled reproduction. The monitoring of populations of this pest by camera traps is a promising technique. These devices capture a large variety of animals, including native species that share similarities with the wild boar, therefore the precise identification of the animal species is essential to control the wild boars. To address this problem, we evaluated 18 different texture analysis methods on their ability to discriminate between two native “bush pigs” species of the brazilian fauna, collared peccary (Pecari tajacu) and white-lipped peccary (Tayassu pecari), and one invasive species, wild boar (Sus scrofa). Results show that species identification is a difficult task due to the similarities among classes, being the distinction between native and invasive species an easier task, and that combining of texture methods improves the accuracy while it diminishes the number of false positives (i.e., native species classified as invasive).

关键词： Animals Task analysis Entropy Cameras Urban areas Shape Histograms

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Screen-space VPL propagation for real-time indirect lighting

Screen-space VPL propagation for real-time indirect lighting

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Vítor M. Aranha Márcio C. F. Macedo Antonio L. Apolinario Federal University of Bahia Salvador BA Brazil

ISBN: (数字)9781728192741

ISBN: (纸本)9781728192758

Reproducing indirect lighting in real time for 3D scenes is a computationally intensive task, but its results add realism and visual fidelity to game-like scenarios and applications. Previous attempts to solve this task explored the use of paraboloid shadow maps for hemispherical visibility queries and Virtual Point Lights (VPLs) for light transport simulations. In our work we aimed at reproducing up to two diffuse bounces of light, while maintaining real-time framerates. We propose an extension to clusterization-based methods in order to sample less VPLs per paraboloid shadow map and capture more bounces of light efficiently. We also propose a projection-aware sampling method to improve sampling efficiency. Our experiments show that, with our approach, it is possible to generate two-bounce VPLs in real time even for low-end commodity GPUs, providing a fast method for indirect illumination.

关键词： Lighting Real-time systems Rendering (computer graphics) Geometry Pipelines Two dimensional displays Light sources

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IDA: Improved Data Augmentation Applied to Salient Object Detection

IDA: Improved Data Augmentation Applied to Salient Object De...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Daniel V. Ruiz Bruno A. Krinski Eduardo Todt Federal University of Parana Brazil

ISBN: (数字)9781728192741

ISBN: (纸本)9781728192758

In this paper, we present an Improved Data Aug-mentation (IDA) technique focused on Salient Object Detection (SOD). Standard data augmentation techniques proposed in the literature, such as image cropping, rotation, flipping, and resizing, only generate variations of the existing examples, providing a limited generalization. Our method combines image inpainting, affine transformations, and the linear combination of different generated background images with salient objects extracted from labeled data. Our proposed technique enables more precise control of the object's position and size while preserving background information. The background choice is based on an inter-image optimization, while object size follows a uniform random distribution within a specified interval, and the object position is intra-image optimal. We show that our method improves the segmentation quality when used for training state-of-the-art neural networks on several famous datasets of the SOD field. Combining our method with others surpasses traditional techniques such as horizontal-flip in 0.52% for F-measure and 1.19% for Precision. We also provide an evaluation in 7 different SOD datasets, with 9 distinct evaluation metrics and an average ranking of the evaluated methods.

关键词： Training Optimization Feature extraction Object detection image segmentation Testing image color analysis

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Profiling Halide DSL with CPU Performance Events for Schedule Optimization 19

Profiling Halide DSL with CPU Performance Events for Schedul...

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23rd brazilian symposium on Programming Languages (SBLP)

作者： Machado, Rafael Ravedutti L. Maidl, Andre Murbach Weingaertner, Daniel Univ Fed Parana Curitiba Parana Brazil Elastic Curitiba Parana Brazil

ISBN: (纸本)9781450376389

Halide is a domain-specific language (DSL) for image processing that enforces a separation of the algorithm and the execution schedule, allowing the generation of specialized code for distinct computer architectures by rewriting only the execution schedule, instead of the whole algorithm. In order to support the creation of good Halide schedules, our work extends the Halide DSL by adding a profiling API that uses the CPU Performance Events to measure events supported by the target processor during the application runtime. The proposed extension offers profiling of the application loop levels and functions' producer and consumer relations, embedding calls to a profiling library in the loop nests of the generated code. It also supports individualized profiling by threads on parallel regions. As a case study we use the PAPI library in order to count events such as L1 cache misses, number of float operations (FLOP) and L3 data volume on an Intel Core i5-7500 CPU, and discuss how the reported results can be used to manually or automatically generate better schedules for an image processing pipeline.

关键词： image processing performance profiler domain specific language

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Nonlinear PCB Compensation Based on Intel® HD graphics for Manufacturing processing

Nonlinear PCB Compensation Based on Intel® HD graphics for ...

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International computer symposium (ICS)

作者： Shau-Yin Tseng Jin-Nan Liu Jian-Wei Chen Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (数字)9781728192550

ISBN: (纸本)9781728192567

Printed Circuit Board (PCB) has the situation of expansion or shrinkage in the manufacturing processing. Moreover, the circuit is more complicated and the line width/spacing is more precise, so that the circuit file becomes very large. Traditionally, four-point registration holes and sub- block are used for the bilinear compensation. Although the traditional methods can be quickly compensated, it cannot enhance the precision. In contrast, using the polynomial compensation can have good precision but time consuming. Moreover, considering the IPC (Industrial Personal computer) heat dissipation and cost issues, GPU (graphics processing Unit) card is rarely used at the factory. In present, Intel CPU contains the Intel® HD graphics which is implemented the bilinear technology by OpenGL texture mapping. Therefore, this paper proposed the polynomial texture mapping algorithm by OpenGL, which calculated the nonlinear straight trace according to the registration holes. The non-uniform interpolation control points are generated by using the slope relationship of the registration holes. Finally, using Intel® HD graphics on multiple IPCs, multi-thread division processing and pipeline processing which can improve the precision of PCB compensation and save the computing time. The experimental results show the proposed method has the smallest XOR (Exclusive-OR) value at the 2.5um resolution and 1um resolution. Meanwhile, the computing time can still maintain 1.749 seconds at the 2.5um resolution and 9.588 seconds at the 1um resolution. In addition, the offset less than 1 pixel of the polynomial texture mapping algorithm accounts for about 65 percent at the 2.5um resolution, and the offset less than 2 pixels of the polynomial texture mapping algorithm accounts for about 57 percent at the 1um resolution. Finally, simulate two IPCs computing time in the image size 510mm x 610mm (resolution is 25400dpi) through the proposed method in this paper, we obtain the 20.618s on IPC1 and 20.30

关键词： graphics Interpolation image resolution Printed circuits graphics processing units Mathematical model Substrates

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Can Exposure, Noise and Compression affect image Recognition? An Assessment of the Impacts on State-of-the-art ConvNets 16

Can Exposure, Noise and Compression affect Image Recognition...

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16th Latin American Robotics symposium (LARS) / 7th brazilian symposium on Robotics (SBR) / 10th Workshop on Robotics in Education (WRE)

作者： Steffens, C. R. Messias, L. R., V Drews-Jr, P. L. J. Botelho, S. S. d C. Univ Fed Rio Grande FURG Ctr Comp Sci Av Italia Km8 Rio Grande Brazil

ISBN: (纸本)9781728142685

Convolutional Neural Networks stand the current state-of-the-art in image recognition, as well as many computer vision tasks. Nevertheless, these architectures have been shown to be vulnerable to image manipulations, which may undermine the reliability and safety of CNN-based models in autonomous and robotic applications. We present a rigorous evaluation of the robustness of several high-level image recognition models and investigate their performance under distinct image distortions. We propose a testing framework which emulates ill exposure conditions, low-range image sensors, lossy compression, as well as commonly observed noise types. One one side results measured in terms of accuracy, precision, and F1-Score, indicate that most CNN models are marginally affected by mild miss-exposure, heavy compression, and Poisson noise. Severe miss-exposure, impulse noise, or signal-dependent noise, on the other side, show a substantial drop in accuracy and precision. A careful evaluation of some typical image distortions, commonly observed in computer vision and machine vision pipelines, provides insights and directions for further developments in the field.

关键词： Autonomous systems Deep learning image processing image recognition image restoration Noise removal Robotics

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Cooperative Object Classification for Driving Applications 30

Cooperative Object Classification for Driving Applications

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30th IEEE Intelligent Vehicles symposium (IV)

作者： Arnold, Eduardo Al-Jarrah, Omar Y. Dianati, Mehrdad Fallah, Saber Oxtoby, David Mouzakitis, Alexandros Univ Warwick WMG Coventry W Midlands England Univ Surrey Ctr Automot Engn Guildford Surrey England Jaguar Land Rover Ltd Coventry W Midlands England

ISBN: (纸本)9781728105604

3D object classification can be realised by rendering views of the same object from different angles and aggregating all the views to build a classifier. Although this approach has been previously proposed for general objects classification, most existing works did not consider visual impairments. In contrast, this paper considers the problem of 3D object classification for driving applications under impairments (e.g. occlusion and sensor noise) by generating an application-specific dataset. We present a cooperative object classification method where multiple images of the same object seen from different perspectives (agents) are exploited to generate more accurate classification. We consider model generalisation capability and its resilience to impairments. We introduce an occlusion model with higher resemblance to real-world occlusion and use a simplified sensor noise model. The experimental results show that the cooperative model, relying on multiple views, significantly outperforms single-view methods and is effective in mitigating the effects of occlusion and sensor noise.

关键词： image classification mobile robots object recognition rendering (computer graphics) robot vision stereo image processing Stereo image processing robot vision image classification Mobile robots object recognition Rendering (computer graphics) Occlusion physical impairment Noise models Visual Impairment Classification Methods multiple image

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A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations?

A Survey on Deep Learning with Noisy Labels: How to train yo...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Filipe R. Cordeiro Gustavo Carneiro Federal Rural University Pernambuco Brazil School of Computer Science Australian Institute for Machine Learning University Adelaide Australia

ISBN: (数字)9781728192741

ISBN: (纸本)9781728192758

Noisy Labels are commonly present in data sets automatically collected from the internet, mislabeled by non-specialist annotators, or even specialists in a challenging task, such as in the medical field. Although deep learning models have shown significant improvements in different domains, an open issue is their ability to memorize noisy labels during training, reducing their generalization potential. As deep learning models depend on correctly labeled data sets and label correctness is difficult to guarantee, it is crucial to consider the presence of noisy labels for deep learning training. Several approaches have been proposed in the literature to improve the training of deep learning models in the presence of noisy labels. This paper presents a survey on the main techniques in literature, in which we classify the algorithm in the following groups: robust losses, sample weighting, sample selection, meta-learning, and combined approaches. We also present the commonly used experimental setup, data sets, and results of the state-of-the-art models.

关键词： Noise measurement Training Symmetric matrices Labeling Deep learning Task analysis Predictive models

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E-Learning Remote Laboratory Station for computer Aided Design 61

E-Learning Remote Laboratory Station for Computer Aided Desi...

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61st International ELMAR symposium

作者： Besic, Ingmar Hodzic, Kerim Karabegovic, Almir Univ Sarajevo Fac Elect Engn Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9781728121819

E-Learning solutions for computer Aided Design (CAD) require high quality graphics for positive impact and high satisfaction. Software tools used for hands-on CAD laboratory exercises depend on dedicated graphics processing Unit (GPU) to deal with complex graphics processing needed to visualize virtual models in real-time. It is challenging to offer the same level of experience to remote users as they usually cannot afford laboratory-level hardware with dedicated GPU nor such hardware can be provided to them as part of their e-Learning experience. In this paper, grouping of average CAD laboratory workstations in pairs is proposed in order to create remote stations capable of performing required CAD graphics processing for remote users while streaming it over the network for a near real-time experience. Remote station captures video and utilizes hardware HEVC encoding, as common capability of high-end dedicated GPUs, to perform low bitrate video streaming with sub-second latency. The remote station concept enables cost-effective extension of average conventional CAD laboratory to an e-Learning remote laboratory for up to 50% additional remote users in respect to the total number of the laboratory workstations.

关键词： e-Learning CAD image processing GPU Video Encoding HEVC

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