The proceedings contain 25 papers. The special focus in this conference is on Soft Computing. The topics include: A multilevel genetic algorithm for the maximum constraint satisfaction problem;models and simulations o...
ISBN:
(纸本)9783319580876
The proceedings contain 25 papers. The special focus in this conference is on Soft Computing. The topics include: A multilevel genetic algorithm for the maximum constraint satisfaction problem;models and simulations of queueing systems;influence of random number generators on GPA-ES algorithm efficiency;genetic algorithm based random selection-rule creation for ontology building;improving artificial fish swarm algorithm by applying group escape behavior of fish;genetic programming algorithm creating and assembling subtrees for making analytical functions;comparison of parallel linear genetic programming implementations;geometric particle swarm optimization and reservoir computing for solar power forecasting;walkSAT based-learning automata for MAX-SAT;a self-adaptive artificial bee colony algorithm with incremental population size for large scale optimization;lie algebra-valued bidirectional associative memories;guaranteed training set for associative networks;Markov chain for author writing style profile construction;maximum traveling salesman problem by adapted neural gas;conjugate gradient algorithms for quaternion-valued neural networks;evaluating suitable job applicants using expert system;a computationally efficient approach for mining similar temporal patterns;estimating prevalence bounds of temporal association patterns to discover temporally similar patterns;an approach for imputation of medical records using novel similarity measure;implementation of particle filters for mobile robot localization;direct point cloud visualization using T-spline with edge detection and development of methods of the fractal dimension estimation for the ecological data analysis.
Cataract is one of the most common diseases that might cause blindness. Previous research shows that cataract occupies almost 50% in severe visually impairments. Fundus image is a significant reference for the diagnos...
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Cataract is one of the most common diseases that might cause blindness. Previous research shows that cataract occupies almost 50% in severe visually impairments. Fundus image is a significant reference for the diagnosis of the cataract disease. The classification of fundus images mainly consists of four parts: pre-processing of fundus images, features extraction, features weighting and classification. In this paper, firstly a whole fundus image is divided into 17 images evenly, secondly features are extracted features from each sub-image, then the feature vectors are weighted with the result of genetic algorithm and finally support vector machine is used to train and classify the fundus images. The experimental result shows that the accuracy of four-class classification can reach 87.52%.
Installed Onboard cameras considering cases of off road unmanned navigating ground vehicles experience severe jitter and vibration. This leads to the prerequisite that the video images acquired from these platforms ne...
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ISBN:
(纸本)9781509047611;9781509047604
Installed Onboard cameras considering cases of off road unmanned navigating ground vehicles experience severe jitter and vibration. This leads to the prerequisite that the video images acquired from these platforms need to be heavily preprocessed to eliminate the jitter induced variations before human analysis. Digital Video stabilization system is the process of using electronic processing to control the image stability. That is, only software algorithms are used rather than hardware components such as motion sensors, actuators or floating lenses to compensate the disturbances. This makes digital stabilization more portable and cost effective among other methods. Digital stabilization can be used for real time and offline applications if the algorithms are optimized. This literature discusses the state of the art in the field of DVS with an implementation aspect of its use in challenging environment of unmanned ground vehicles where due to the dynamic nature of the vehicle, vibrations and oscillations are affect the camera resulting in a shaky and unstable video feed.
Modern scientific instruments, such as detectors at synchrotron light sources, can generate data at 10s of GB/sec. Current experimental protocols typically process and validate data only after an experiment has comple...
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ISBN:
(纸本)9781538626863
Modern scientific instruments, such as detectors at synchrotron light sources, can generate data at 10s of GB/sec. Current experimental protocols typically process and validate data only after an experiment has completed, which can lead to undetected errors and prevents online steering. Real-time data analysis can enable both detection of, and recovery from, errors, and optimization of data acquisition. We thus propose an autonomous stream processing system that allows data streamed from beamline computers to be processed in real time on a remote supercomputer, with a control feed-back loop used to make decisions during experimentation. We evaluate our system using two iterative tomographic reconstruction algorithms and varying data generation rates. These experiments are performed in a real-world environment in which data are streamed from a light source to a cluster for analysis and experimental control. We demonstrate that our system can sustain analysis rates of hundreds of projections per second by using up to 1,200 cores, while meeting stringent data quality constraints.
This paper focuses on the lateral chromatic aberration correction to eliminate the chromatic aberration effect with imageprocessing methods. images were captured by the portable non-mydriatic eye fundus orbital camer...
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ISBN:
(纸本)9781785616525
This paper focuses on the lateral chromatic aberration correction to eliminate the chromatic aberration effect with imageprocessing methods. images were captured by the portable non-mydriatic eye fundus orbital camera that has no achromatic lenses. imageprocessing methods for correcting the lateral chromatic aberration effect correction try to scale the fringed colour channels so that all channels spatially overlap each other correctly in the final image. Classical algorithms are based on different patterns evaluation to derive an appropriate model for the correction. In this research, we have shown that these patterns can be successfully replaced with a map of detected eye fundus blood vessels. A comparison of the pattern (chessboard and circles) based method and the proposed method was accomplished using five different correction models: simple, affine, projective and two radial ones with one and two coefficients. Quality of images was measured and evaluated using Blur Metric, Chromatic Zipper and Achromatic Zipper metrics. The results have showed that the chromatic aberration correction using both methods have a significantly improved quality of the original images.
The vibroacoustic method of device diagnostics is most often based on spectrum analysis of digitally recorded vibration signal of their mechanical elements. In the steady-state, depending on the test object, the signa...
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The vibroacoustic method of device diagnostics is most often based on spectrum analysis of digitally recorded vibration signal of their mechanical elements. In the steady-state, depending on the test object, the signal may contain only fundamental frequency and harmonics. Then, in case of poor mechanical condition, diagnostic signal contains also some foreign frequencies. Using signal of finite length for computing its spectrum causes some deviations in spectrum structure. It can be the reason for misinterpretation because of array frequencies occurring in DFT, which in fact do not exist in the signal and existing frequencies, which have incorrect amplitude. To reduce this effect, the window function can be used. Taking into consideration the special spectral structure of diagnostic signals in the steady-state, it is possible to adjust parameters of signals in such a way to eliminate any distortion for regular frequencies. For this purpose, if further analysis requires a fixed number of signal samples, by signal resampling, spectral resolution can be adjusted to the harmonics existing in the signal, especially, when processed are signals already recorded with unwanted sampling frequencies.
In this paper, imageprocessingalgorithms designed in Zynq SoC using the Vivado HLS tool are presented and compared with hand-coded designs. In Vivado HLS, the designer has the opportunity to employ libraries similar...
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ISBN:
(纸本)9781509045655
In this paper, imageprocessingalgorithms designed in Zynq SoC using the Vivado HLS tool are presented and compared with hand-coded designs. In Vivado HLS, the designer has the opportunity to employ libraries similar to OpenCV, a library that is well-known and wide used by software designers. The algorithms are compared in terms of area resources in two conditions: using the libraries and not using the libraries. The case studies are Data Binning, a Step Row Filter and a Sobel Filter. These algorithms have been selected because they are very common in the field of imageprocessing and they have high computational complexity. The main benefit of the Vivado HLS tool is the reduction in time-to-market. On the other hand, when a software designer hand-codes the design, the use of imageprocessing libraries similar to OpenCV helps to reduce development time even further because software designers are familiar with them. However, using these kinds of libraries significantly increases the necessary FPGA resources.
DNA microarrays play a very important role in clinical diagnosis to find out the expression levels of large number of genes simultaneously and mutation of the genes in a given organism. This raw microarray fluorescenc...
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ISBN:
(纸本)9781509047611;9781509047604
DNA microarrays play a very important role in clinical diagnosis to find out the expression levels of large number of genes simultaneously and mutation of the genes in a given organism. This raw microarray fluorescence signal has a lot of noise, which may originate from auto fluorescence, background noise, non specific binding and detector itself. In this paper, we tried to exploit the different denoising algorithms based on the diffusion filtering and perform their comparative study to find out the best method suitable for low intensity images of microarray. A quantitative measure of image is provided by signal to noise ratio (SNR) of image and visual quality of denoised images compared with universal quality index. This helps to reduce the quantification errors in calculating the expression levels in individual microarray spots and for better representation of the microarray data for clinical diagnosis.
Background extraction is a fundamental task present in most computer vision applications such as video surveillance, optical motion capture or multimedia applications. In this paper we explore a particular foreground ...
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ISBN:
(纸本)9781509049929
Background extraction is a fundamental task present in most computer vision applications such as video surveillance, optical motion capture or multimedia applications. In this paper we explore a particular foreground segmentation method based on the well-known Pixel-based Adaptive Segmenter (PBAS) algorithm, proposing modifications that will ease the hardware implementation. Also, the figures of merit of a focal-plane approach for foreground segmentation are studied through the impact of typical temporal and spatial noise sources present in the processing elements of smart image sensors such as leakage currents from analog memories or fixed pattern noise (FPN) from mismatch.
As the successor of H.264, High Efficient Video Coding (HEVC) standard includes various novel techniques, including Coding Tree Unit (CTU) structure and additional angular modes used in intra coding. These new techniq...
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ISBN:
(纸本)9781509063451
As the successor of H.264, High Efficient Video Coding (HEVC) standard includes various novel techniques, including Coding Tree Unit (CTU) structure and additional angular modes used in intra coding. These new techniques promote the coding efficiency on one hand, while increasing the computational complexity significantly on the other hand. In this paper, we propose a fast intra block partitioning algorithm for HEVC to reduce the coding complexity, based on the statistical cost and corner detection algorithm. A block is considered as a multiple gradients region which will be split into multiple small ones, as the corner points are detected inside the block. A block without corner points existing is treated as being non-split when its RD cost is small according the statistics of the previous frames. The proposed fast algorithm achieves nearly 63% encoding time reduction with 3.42%, 2.80%, and 2.53% BD-Rate loss for Y, U, and V components, averagely. The experimental results show that the proposed method is efficient to fast decide the block partitioning in intra coding of HEVC, even though only static parameters are applied to all test sequences.
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