A rigid registration is a crucial initial step for a correct deformable medical image registration. In this work, we propose rigid registration method resistant to large deformations and missing data. The proposed met...
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ISBN:
(纸本)9781538669792
A rigid registration is a crucial initial step for a correct deformable medical image registration. In this work, we propose rigid registration method resistant to large deformations and missing data. The proposed method is based on the bones segmentation, feature matching and outliers elimination inspired by traditional computer vision approach. The method is compared to other state-of-the- art algorithms, the iterative closest point and intensity-based registration using widely available dataset. The proposed algorithm does not fail into local minima and reconstructs correct deformations for average vector length greater than 150 mm and data overlap ratio less than 50%, where currently applied methods fail. The algorithm is evaluated using angle and magnitude errors between corresponding deformation vectors, Hausdorff distance between bone segmentations and resistance to fail into local minima.
In this paper, hardware implementation of corner detection at real time video signals using Harris filter based on FPGA is explained. Corner detection is an elemantary and fundamental tool for image segmentation and f...
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ISBN:
(纸本)9781538615010
In this paper, hardware implementation of corner detection at real time video signals using Harris filter based on FPGA is explained. Corner detection is an elemantary and fundamental tool for image segmentation and feature extraction like edge detection. Very high speed hardware like FPGA's are used to implement the image and video processingalgorithms for improving the performance of processingsystems. algorithms are implemented on the Xilinx Zynq 7000. The video input signals come from a laptop's HDMI interface to FPGA in order to filter and the detected corners are displayed on a HDMI display screen.
One algorithin for thresholding using a histogram median is presented in this paper. The algorithm is named HisMedian and it is implemented on Java. It is also proposed a taxonomy of thresholding algorithms based on a...
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ISBN:
(纸本)9781450364256
One algorithin for thresholding using a histogram median is presented in this paper. The algorithm is named HisMedian and it is implemented on Java. It is also proposed a taxonomy of thresholding algorithms based on a method for defining threshold value as a real color of image or calculated color's value. According to the proposed taxonomy a set of popular thresholding algorithms (including HisMedian) is experimentally evaluated using three test images. The experimental results show that if a histogram is bimodal then the algorithms which use real color(s) from the image as a threshold(s) achieve better results than algorithms which use calculated value(s) as a threshold(s).
Modern neural network-based algorithms are able to produce highly accurate depth estimates from stereo image pairs, nearly matching the reliability of measurements from more expensive depth sensors. However, this accu...
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ISBN:
(数字)9781728165530
ISBN:
(纸本)9781728165547
Modern neural network-based algorithms are able to produce highly accurate depth estimates from stereo image pairs, nearly matching the reliability of measurements from more expensive depth sensors. However, this accuracy comes with a higher computational cost since these methods use network architectures designed to compute and process matching scores across all candidate matches at all locations, with floating point computations repeated across a match volume with dimensions corresponding to both space and disparity. This leads to longer running times to process each image pair, making them impractical for real-time use in robots and autonomous vehicles. We propose a new stereo algorithm that employs a significantly more efficient network architecture. Our method builds an initial match cost volume using traditional matching costs that are fast to compute, and trains a network to estimate disparity from this volume. Crucially, our network only employs per-pixel and two-dimensional convolution operations: to summarize the local match information at each location as a lowdimensional feature vector, and to spatially process these "cost-signature" features to produce a dense disparity map. Experimental results on KITTI show that our method delivers competitive accuracy at significantly higher speeds- running at 48 frames per second on a modern GPU.
Most of the applications in mobile robots use the image data from the monitoring system to compile algorithms. The undesired movement in the video is an obstacle to compute commands, and it requires to reduce this mot...
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The aim of this research is to develop an appropriate experimental setting and to explore the possibilities for objective automatic and express assessment of some appearance indicators of beer quality using computer v...
The aim of this research is to develop an appropriate experimental setting and to explore the possibilities for objective automatic and express assessment of some appearance indicators of beer quality using computer vision techniques. The goal of the research will be achieved by developing a computer vision system, including a hardware module for obtaining primary information and a software module for processing primary information and extracting the desired characteristics through algorithms based on adapted imageprocessing methods.
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchi...
ISBN:
(纸本)9783319911915
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchical fuzzy deep leaning networks for predicting human behavior in strategic setups;fuzzy-Expert system for customer behavior prediction;a binary grasshopper algorithm applied to the knapsack problem;artificial neural networks implementing maximum likelihood estimator for passive radars;using query expansion for cross-lingual mathematical terminology extraction;text summarization techniques for meta description generation in process of search engine optimization;integration of models of adaptive behavior of ant and bee colony;optimization of multistage tourist route for electric vehicle;FARIP: Framework for artifact removal for imageprocessing using JPEG;enhancing stratified graph sampling algorithms based on approximate degree distribution;MIC-KMeans: A maximum information coefficient based high-dimensional clustering algorithm;DACC: A data exploration method for high-dimensional data sets;multi-targets tracking of multiple instance boosting combining with particle filtering;An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel;Hyper-heuristical particle swarm method for MR images segmentation;A hybrid SAE and CNN classifier for motor imagery EEG classification;semantic bookmark system for dynamic modeling of users browsing preferences;models, algorithms and monitoring system of the technical condition of the launch vehicle “Soyuz-2” at all stages of its life cycle;proactive management of complex objects using precedent methodology;SOPA: Search optimization based predictive approach for design optimization in finFET/SRAM;hierarchical system for evaluating professional competencies using Takagi-Sugeno rules.
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchi...
ISBN:
(纸本)9783319911885
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchical fuzzy deep leaning networks for predicting human behavior in strategic setups;fuzzy-Expert system for customer behavior prediction;a binary grasshopper algorithm applied to the knapsack problem;artificial neural networks implementing maximum likelihood estimator for passive radars;using query expansion for cross-lingual mathematical terminology extraction;text summarization techniques for meta description generation in process of search engine optimization;integration of models of adaptive behavior of ant and bee colony;optimization of multistage tourist route for electric vehicle;FARIP: Framework for artifact removal for imageprocessing using JPEG;enhancing stratified graph sampling algorithms based on approximate degree distribution;MIC-KMeans: A maximum information coefficient based high-dimensional clustering algorithm;DACC: A data exploration method for high-dimensional data sets;multi-targets tracking of multiple instance boosting combining with particle filtering;An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel;Hyper-heuristical particle swarm method for MR images segmentation;A hybrid SAE and CNN classifier for motor imagery EEG classification;semantic bookmark system for dynamic modeling of users browsing preferences;models, algorithms and monitoring system of the technical condition of the launch vehicle “Soyuz-2” at all stages of its life cycle;proactive management of complex objects using precedent methodology;SOPA: Search optimization based predictive approach for design optimization in finFET/SRAM;hierarchical system for evaluating professional competencies using Takagi-Sugeno rules.
As technology progresses, monetary transaction systems around the world are being continuously developed. Artificial intelligence as part of machine learning, especially, emerges as a new trend being used in transacti...
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As technology progresses, monetary transaction systems around the world are being continuously developed. Artificial intelligence as part of machine learning, especially, emerges as a new trend being used in transactions automation. This research is written with a purpose to propose a comprehensive comparison of accuracy, in recognizing denomination of authentic Indonesian Banknotes (Rupiah) using imageprocessing methods and machine learning algorithms. This research is comparing accuracy between some classification systems designed using several known classifiers, using three kinds of image resolutions. From this research, KNN produced 100% accuracy, while the accuracy for SVM varied between 12.5 to 100% depending on the kernel used.
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchi...
ISBN:
(纸本)9783319911854
The proceedings contain 141 papers. The special focus in this conference is on Computer Science On-line. The topics include: Financial knowledge instantiation from semi-structured, heterogeneous data sources;hierarchical fuzzy deep leaning networks for predicting human behavior in strategic setups;fuzzy-Expert system for customer behavior prediction;a binary grasshopper algorithm applied to the knapsack problem;artificial neural networks implementing maximum likelihood estimator for passive radars;using query expansion for cross-lingual mathematical terminology extraction;text summarization techniques for meta description generation in process of search engine optimization;integration of models of adaptive behavior of ant and bee colony;optimization of multistage tourist route for electric vehicle;FARIP: Framework for artifact removal for imageprocessing using JPEG;enhancing stratified graph sampling algorithms based on approximate degree distribution;MIC-KMeans: A maximum information coefficient based high-dimensional clustering algorithm;DACC: A data exploration method for high-dimensional data sets;multi-targets tracking of multiple instance boosting combining with particle filtering;An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel;Hyper-heuristical particle swarm method for MR images segmentation;A hybrid SAE and CNN classifier for motor imagery EEG classification;semantic bookmark system for dynamic modeling of users browsing preferences;models, algorithms and monitoring system of the technical condition of the launch vehicle “Soyuz-2” at all stages of its life cycle;proactive management of complex objects using precedent methodology;SOPA: Search optimization based predictive approach for design optimization in finFET/SRAM;hierarchical system for evaluating professional competencies using Takagi-Sugeno rules.
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