Mainly when applied in the underwater environment, sonar simulation requires great computational effort due to the complexity of acoustic physics. Simulation of sonar operation allows evaluating algorithms and control...
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Mainly when applied in the underwater environment, sonar simulation requires great computational effort due to the complexity of acoustic physics. Simulation of sonar operation allows evaluating algorithms and control systems without going to the real underwater environment;that reduces the costs and risks of in-field experiments. This paper tackles with the problem of real-time underwater imaging sonar simulation by using the OpenGL shading language chain on GPU. Our proposed system is able to simulate two main types of acoustic devices: mechanical scanning imaging sonars and forward-looking sonars. The underwater scenario simulation is performed based on three frameworks: (i) OpenSceneGraph reproduces the ocean visual effects, (ii) Gazebo deals with physical forces, and (iii) the Robot Construction Kit controls the sonar in underwater environments. Our system exploits the rasterization pipeline in order to simulate the sonar devices, which are simulated by means of three parameters: the pulse distance, the echo intensity and the sonar field-of-view, being all calculated over observable objects shapes in the 3D rendered scene. Sonar-intrinsic operational parameters, speckle noise and object material properties are also considered as part of the acoustic image. Our evaluation demonstrated that the proposed system is able to operate close to or faster than the real-world devices. Also, our method generates visually realistic sonar images when compared with real-world sonar images of the same scenes. (C) 2017 Elsevier Ltd. All rights reserved.
The committee of The iv International conference on Information Technology and Nanotechnology (ITNT-2018) would like to express our greatest gratitude to Samara National Research University and imageprocessing System...
The committee of The iv International conference on Information Technology and Nanotechnology (ITNT-2018) would like to express our greatest gratitude to Samara National Research University and imageprocessingsystems Institute of RAS - branch of FSRC 'Crystallography and Photonics' RAS for hosting the conference, to sponsors and partners for financial and informational support of the event.
The proceedings contain 69 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Multimodal based clouds computing systems for healthcare and risk...
ISBN:
(纸本)9783319490724
The proceedings contain 69 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Multimodal based clouds computing systems for healthcare and risk forecasting based on subjective analysis;telematics and advanced transportation services;toward affective speech-to-speech translation;a computer vision based machine for walnuts sorting using robot operating system;a fpga based two level optimized local filter designfor high speed imageprocessing applications;a frequency dependent investigation of complex shear modulus estimation;a method to enhance the remote sensing images based on the local approach using kmeans algorithm;a method for clustering and identifying http automated software communication;a new neuro-fuzzy inference system for insurance forecasting;a new schema to identify s-farnesyl cysteine prenylation sites with substrate motifs;a novel framework based on deep learning and unmanned aerial vehicles to assess the quality of rice fields;a semi-supervised learning method for hybrid filtering;a study on fitness representation in genetic programming;an evaluation of hand pyramid structure for hand representation based on kernels;an exploratory study on students’ performance classification using hybrid of decision tree and naïve bayes approaches;an iterative method to solve boundary value problems with irregular boundary conditions;classifying human body postures by a support vector machine with two simple features;comparing modified pso algorithms for mrs in unknown environment exploration and estimation localization in wireless sensor network based on multi-objective grey wolf optimizer.
The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations a...
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ISBN:
(数字)9781510609686
ISBN:
(纸本)9781510609679;9781510609686
The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations and also of interest in many digital signal processing applications. In [Zhao 14] we have reported that a given 2D input image with rectangular shape/boundary, in general, results in a parallelogram output sampling grid (generally in an affine coordinates rather than in a Cartesian coordinates) thus limiting the further calculations, e.g. inverse transform. One possible solution is to use the interpolation techniques;however, it reduces the speed and accuracy of the numerical approximations. To alleviate this problem, in this paper, some constraints are derived under which the output samples are located in the Cartesian coordinates. Therefore, no interpolation operation is required and thus the calculation error can be significantly eliminated.
Multispectral face recognition systems are widely used in various access control applications. The vulnerability of multispectral face recognition sensors towards low-cost Presentation Attack Instrument (PAI) such as ...
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ISBN:
(纸本)9780996452700
Multispectral face recognition systems are widely used in various access control applications. The vulnerability of multispectral face recognition sensors towards low-cost Presentation Attack Instrument (PAI) such as printed photos used in attacks has emerged as a serious security threat. In this paper, we present a novel framework to detect presentation attacks against an extended multispectral face sensor. The proposed framework stems from the idea of exploring the complementary information available from different bands of an extended multispectral face sensor. To this extent, two different frameworks are proposed where the first framework is based on image fusion and the second builds on the Presentation Attack Detection (PAD) score level fusion. Extensive experiments are carried out on the extended multispectral face sensor database comprising of 50 subjects with two different presentation attacks generated using the printed photo artefacts. The obtained results indicate the superior performance of the PAD score level fusion on detecting both known and unknown attacks.
Infrared (IR) imaging has the potential to enable more robust action recognition systems compared to visible spectrum cameras due to lower sensitivity to lighting conditions and appearance variability. While the actio...
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ISBN:
(纸本)9781538607336
Infrared (IR) imaging has the potential to enable more robust action recognition systems compared to visible spectrum cameras due to lower sensitivity to lighting conditions and appearance variability. While the action recognition task on videos collected from visible spectrum imaging has received much attention, action recognition in IR videos is significantly less explored. Our objective is to exploit imaging data in this modality for the action recognition task. In this work, we propose a novel two-stream 3D convolutional neural network (CNN) architecture by introducing the discriminative code layer and the corresponding discriminative code loss function. The proposed network processes IR image and the IR-based optical flow field sequences. We pretrain the 3D CNN model on the visible spectrum Sports-1M action dataset and finetune it on the Infrared Action Recognition (InfAR) dataset. To our best knowledge, this is the first application of the 3D CNN to action recognition in the IR domain. We conduct an elaborate analysis of different fusion schemes (weighted average, single and double-layer neural nets) applied to different 3D CNN outputs. Experimental results demonstrate that our approach can achieve state-of-the-art average precision (AP) performances on the InfAR dataset: (1) the proposed two-stream 3D CNN achieves the best reported 77.5% AP, and (2) our 3D CNN model applied to the optical flow fields achieves the best reported single stream 75.42% AP.
The digital image watermarking technology is widely used to protect intellectual property and to authenticate digital contents in the network environment. The aim of the paper is to invoke the improved Laplacian Pyram...
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ISBN:
(纸本)9781509022922
The digital image watermarking technology is widely used to protect intellectual property and to authenticate digital contents in the network environment. The aim of the paper is to invoke the improved Laplacian Pyramid transform to develop a new image watermarking scheme. Specifically, the host image is decomposed and reconstructed by using the improved Laplacian Pyramid transform. Then, the mid frequency subband data with the appropriate level and strength factor are chosen to embed the watermark. Finally, we conduct experiments to investigate the invisibility and robustness of the proposed algorithm. To measure the invisibility and the robustness of the algorithms, we use the peak signal-to-noise ratio (PSNR) and normalized correlation (NC) as performance metrics. Experimental results demonstrate that invisibility and robustness are guaranteed. The proposed algorithm outperforms one based on curvelets for the lossy JPEG compression attack in terms of invisibility and robustness.
The images captured by a camera is saved or otherwise sent over the internet without encryption. If the camera is stolen, then all the images stored inside it will be stolen by others. For real time applications to im...
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ISBN:
(纸本)9781538619605
The images captured by a camera is saved or otherwise sent over the internet without encryption. If the camera is stolen, then all the images stored inside it will be stolen by others. For real time applications to impose security, image is to be captured, compressed and encrypted in the camera itself. To resolve this issue, chaotic based image encryption is proposed while capturing the image. Experiments are made in NI Smart Camera and analysed with various measures to prove the efficacy of the proposed algorithm.
In this paper, we discuss a method for automatic programming of inspection imageprocessing. In the industrial field, automatic program generators or expert systems are expected to shorten a period required for develo...
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ISBN:
(数字)9781510611221
ISBN:
(纸本)9781510611214;9781510611221
In this paper, we discuss a method for automatic programming of inspection imageprocessing. In the industrial field, automatic program generators or expert systems are expected to shorten a period required for developing a new appearance inspection system. So-called "imageprocessing expert system" have been studied for over the nearly 30 years. We are convinced of the need to adopt a new idea. Recently, a novel type of evolutionary algorithms, called genetic network programming (GNP), has been proposed. In this study, we use GNP as a method to create an inspection imageprocessing logic. GNP develops many directed graph structures, and shows excellent ability of formulating complex problems. We have converted this network program model to imageprocessing Network Programming (IPNP). IPNP selects an appropriate imageprocessing command based on some characteristics of input image data and processing log, and generates a visual inspection software with series of imageprocessing commands. It is verified from experiments that the proposed method is able to create some inspection imageprocessing programs. In the basic experiment with 200 test images, the success rate of detection of target region was 93.5%.
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