This book constitutes the refereed conference proceedings of the 8th International conference on image and Graphics, ICIG 2015 held in Tianjin, China, in August 2015. The 164 revised full papers and 6 special issue pa...
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ISBN:
(数字)9783319219783
ISBN:
(纸本)9783319219776
This book constitutes the refereed conference proceedings of the 8th International conference on image and Graphics, ICIG 2015 held in Tianjin, China, in August 2015. The 164 revised full papers and 6 special issue papers were carefully reviewed and selected from 339 submissions. The papers focus on various advances of theory, techniques and algorithms in the fields of images and graphics.
This publication contains 249 conference papers. The following topics are dealt with: protocol and applications and packet switching;TDX-10 digital switching system technology;artificial intelligence and expert system...
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This publication contains 249 conference papers. The following topics are dealt with: protocol and applications and packet switching;TDX-10 digital switching system technology;artificial intelligence and expert systems;imageprocessing;computer architecture;software for parallel processing;token passing LAN and applications;optimization and neural networks;digital modulation and modems;functional programming languages;architectures for parallel processing;application and implementation of Petri net concepts;signal processing and filters;array spectral analysis;advanced communication networks;TROPICO digital switching system;high performance computing theory and applications;pattern recognition;fault tolerant computing;instrumentation and process control;data communication networks;speech analysis and recognition;computer hardware systems;robotics and automation;mobile radio;theoretical computer science and algorithms;distributed processing;LAN/WAN networking;applied expert systems;coding;C-DOT digital switching system;power delivery systems;rural communication;radar;parallel execution of functional programs;VLSI, ASICS and devices;transmission media and communication systems;office automation and databases;program transformation, synthesis and analysis;and power electronics.
Multimodality images obtained from different medical imaging systems such as magnetic resonance (MR), computed tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomo...
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ISBN:
(纸本)0819417823
Multimodality images obtained from different medical imaging systems such as magnetic resonance (MR), computed tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomography (SPECT) provide largely complementary characteristic or diagnostic information. Therefore, it is an important research objective to `fuse' or combine this complementary data into a composite form which would provide synergistic information about the objects under examination. An important first step in the use of complementary fused images is 3D image registration, where multi-modality images are brought into spatial alignment so that the point-to-point correspondence between image data sets is known. Current research in the field of multimodality image registration has resulted in the development and implementation of several different registration algorithms, each with its own set of requirements and parameters. Our research has focused on the development of a general paradigm for measuring, evaluating and comparing the performance of different registration algorithms. Rather than evaluating the results of one algorithm under a specific set of conditions, we suggest a general approach to validation using simulation experiments, where the exact spatial relationship between data sets is known, along with phantom data, to characterize the behavior of an algorithm via a set of quantitative image measurements. This behavior may then be related to the algorithm's performance with real patient data, where the exact spatial relationship between multimodality images is unknown. Current results indicate that our approach is general enough to apply to several different registration algorithms. Our methods are useful for understanding the different sources of registration error and for comparing the results between different algorithms.
Detecting and segmenting moving object is an important subject in computer visual analysis. Firstly, this paper discusses algorithms of detecting moving target from static background in video sequences. Secondly, as t...
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ISBN:
(纸本)9780769532783
Detecting and segmenting moving object is an important subject in computer visual analysis. Firstly, this paper discusses algorithms of detecting moving target from static background in video sequences. Secondly, as the existing mixture Gaussian models can't solve the problems such as ghost and real-time application, a new method based on moving edge detection of difference between adjacent frames is proposed. Experimental results show that the proposed algorithm can get exact moving edge from complex background and eliminate disturbing of background efficiently, with operating time reducing dramatically. Finally, by filling the edge map the target foreground object can be segregated completely. Combined with mathematical morphology, it can reduce noise and smooth out gaps.
Two ways of efficient features construction for linear local description of one-dimension signal are considered in the work. These approaches use global optimization algorithms for determination of feature parameters....
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ISBN:
(纸本)9780889868410
Two ways of efficient features construction for linear local description of one-dimension signal are considered in the work. These approaches use global optimization algorithms for determination of feature parameters. The comparison of these ways is performed as well as the comparison with the way which uses pseudogradient algorithm. The quality criterion used for comparison is the value which describes cumulatively the correlation degree of sequences that define impulse responses of features computation algorithm and the precision of representation of given signals set with the help of this sequences.
Computer assistance in Minimally Invasive Surgery is a very active field of research. Many systems designed for Computer Assisted Surgery require information about the instruments' positions and orientations. Out ...
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ISBN:
(纸本)9780819480248
Computer assistance in Minimally Invasive Surgery is a very active field of research. Many systems designed for Computer Assisted Surgery require information about the instruments' positions and orientations. Out main focus lies on tracking a laparoscopic ultrasound probe to generate 3D ultrasound volumes. State-of-the-art tracking methods such as optical or electromagnetic tracking systems measure pose with respect to a fixed extra-body coordinate system. This causes inaccuracies of the reconstructed ultrasound volume in the case of patient motion, e.g. due to respiration. We propose attaching an endoscopic camera to the ultrasound probe and calculating the camera motion from the video sequence with respect to the organ surface. We adapt algorithms developed for solving the relative pose problem to recreate the camera path during the ultrasound sweep over the organ. By this image-based motion estimation camera motion can only be determined up to an unknown scale factor, known as the depth-speed-ambiguity. We show, how this problem can be overcome in the given scenario, exploiting the fact, that the distance of the camera to the organ surface is fixed and known. Preprocessing steps are applied to compensate for endoscopic image quality deficiencies.
The real-time image forming in future, high-end synthetic aperture radar systems is an example of an application that puts new demands on computer architectures. The initial question is whether it is at all possible t...
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Color Filter Arrays (CFA) are essential components of digital cameras and image sensors to capture the color information needed to produce full-color images from only a single image sensor per pixel. Many methods and ...
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ISBN:
(纸本)9798350388787;9798350388770
Color Filter Arrays (CFA) are essential components of digital cameras and image sensors to capture the color information needed to produce full-color images from only a single image sensor per pixel. Many methods and algorithms have been proposed to recover the missing color information of CFAs. In this work, we use a simplified version of the Theshold-based Variable Number of Gradients algorithm proposed by Chang et al. to estimate the full-color information from Bayer images. We also show that the slight modification to algorithm does not effect images quality while making it more compatible with hardware. We propose an efficient implementation of the algorithm that reduces the number of calculations per pixel at the cost of increased memory resources. Our implementation targets an imageprocessing pipeline in an FPGA platform which is short on LUTs and FF resources but has DSPs and BRAMs to spare. We buffer the absolute differences and average color components to be shared and re-used between neighboring pixels, on two levels: within the same row, and between different rows. The latter strategy reduces the number of absolute differences calculated every cycle from 32 to 4 and average color components from 32 to 6. However, the memory requirements are increased from storing 4 image rows to 18 image rows. We implement the solutions on an FPGA using high-level synthesis (HLS) and optimize it to further reduce resources.
This paper describes an automatic computer searching system for detecting clustered microcalcifications. A fuzzy classification modeling was employed to extract each suspected microcalcification possessing similar phy...
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ISBN:
(纸本)0819420859
This paper describes an automatic computer searching system for detecting clustered microcalcifications. A fuzzy classification modeling was employed to extract each suspected microcalcification possessing similar physical parameters. Therefore, only those possible classes were evaluated using a sophisticated convolution neural network which requires a great deal of computation and serves as a discriminator. Based on the detected spots, many of them are true microcalcifications, the computer can easily make a determination when 5 spots are located within a defined region. However, when a cluster consists of only two to four suspicious spots a fuzzy function was used to determine the inclusion of other spots near the cluster. This can be very important for the detection of subtle cases. The membership of the latter fuzzy function was composed of the distance between the suspected spots as well as the output values of the convolution neural network. We have tested the improved algorithms on our research database consisting of 45 mammograms. The results indicated that the fuzzy classification modeling decreased the number of false-positives from 2,874 to 1,067 suspected spots per image without increasing any false-negative detection. The over-all performance in the detection of clustered microcalcifications through the updated algorithms was 90% sensitivity at 0.5 false-positive per image. The computation time using a DEC-Alpha workstation was decreased from 5 minutes to about 3 minutes per image.
The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information ...
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ISBN:
(纸本)0819442763
The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information and therefore helps to compress the information of ISCI. In this paper, an isotherm extraction method is presented. The main aggregate of clouds can be segmented based on mathematical morphology. Talgorithm and IP algorithm are then applied to extract the isotherms from the main aggregate of clouds. A concrete example for the extraction of isotherm based on IBM SP2is described. Study of the result shows that this is a highly efficient algorithm. It can be used in feature extractions of infrared images for weather forecasts.
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