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20th symposium ON signal processing, imageS AND COMPUTER VISION (STSIVA)

作者： Pardo, Camilo Sosa, Luis Rojas, Lina Lopez, Jonathan Monsalve, Julian Univ Santo Tomas Bogota Colombia

ISBN: (纸本)9781467394611

The electronic and computational development has helped to create many new applications where the principal idea is obtaining better results in case of an emergency. Over time, we have investigated about new processes and strategies to analyze data, and how to use by audiovisual media to teach people to respond to emergency response, or any natural disaster as a seism. Using systems based on analysis and processing of images and the new mobile applications, we can create a new tool used in case of emergency. This new application will give us the instructions to evacuate safety, taking care of everyone's physical integrity. We have developed this project to find and implement solutions to the problems that can be faced in an emergency or a natural disaster, because in those cases we need to evacuate a zone. This new application will give faster and safer ways of getting out of the dangerous places getting images from them and sending the information to the person in danger. Also, this application will be able to alert the people closer to an emergency exit letting them know the actual situation of it. It will allow the people to move through different exit routs in case of collapse, or any impediment that might be blocking an exit. Thus, the evacuation will be safer and will get better results, saving more people's lives.

关键词： disasters emergency management image processing mobile computing USTA Tunja audiovisual media computational development data analysis electronic development emergency exit emergency response evacuation routes exit routes image analysis mobile applications natural disaster safe evacuation system prototype Databases image edge detection Mobile applications Mobile communication Servers Software Mobile Applications Natural Disasters audiovisual media image processing Edge detection Emergency Services Emergency Egress crisis management mobile communication Servers Mobile Computing Persons Database Evacuation EMERGENCY RESPONSE

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Application of particle swarm optimization and snake model hybrid on medical imaging

Application of particle swarm optimization and snake model h...

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symposium Series on computational intelligence, ieee SSCI 2011 - 2011 ieee 3rd International Workshop on computational intelligence in Medical Imaging, CIMI 2011

作者： Shahamatnia, Ehsan Ebadzadeh, Mohamad Mehdi Universidade Nova de Lisboa FCT-UNINOVA Caparica 2829-516 Portugal Electrical and Computer Eng. Department Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9781612843360

Active contour model has been widely used in image processing applications such as boundary delineation, image segmentation, stereo matching, shape recognition and object tracking. In this paper a novel particle swarm optimization scheme has been introduced to evolve snake over time in a way to reduce time complexity while improving quality of results. Traditional active contour models converge slowly and are prone to local minima due to their complex nature. Various evolutionary techniques including genetic algorithms, particle swarm optimization and predator prey optimization have been successfully employed to tackle this problem. Most of these methods are general problem solvers that, more or less, formulate the snake model equations as a minimization problem and try to optimize it. In contrary, our proposed approach integrates concepts from active contour model into particle swarm optimization so that each particle will represent a snaxel of the active contour. Canonical velocity update equation in particle swarm algorithm is modified to embrace the snake kinematics. This new model makes it possible to have advantages of swarm based searching strategies and active contour principles all together. Aptness of the proposed approach has been examined through several experiments on synthetic and real world images of CT and MRI images of brain and the results demonstrate its promising performance particularly in handling boundary concavities and snake initialization problems. © 2011 ieee.

关键词： image segmentation

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An improved Canny edge detector against impulsive noise based on CIELAB space

An improved Canny edge detector against impulsive noise base...

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International symposium on intelligence Information processing and Trusted Computing

作者： Zeng, Jun Li, Dehua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769541969

The traditional Canny edge detector is designed to detect the edges of gray image, the color image must be converted to gray image, this method only uses the luminance imformation of color image, and don't take into account the chroma information, therefore, it misses some edges. In this paper, an improved Canny edge detector against impulsive noise based on CIELAB space is proposed, the color image is first converted from RGB space to CIELAB space, it uses switching vector median filter to remove impulsive noise, and then caculates the color difference and direction, non-maximal suppression is used to refine the color difference image, finally, it extracts edges by double-threshold method. The experimental results show that the proposed method has better performance on impulsive noise suppression and detects more edges than the traditional Canny edge detector. © 2010 ieee.

关键词： Median filters

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An iterative fuzzy segmentation algorithm for recognizing an odor source in near shore ocean environments

An iterative fuzzy segmentation algorithm for recognizing an...

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International symposium on computational intelligence in Robotics and Automation

作者： Li, Wei Calif State Univ Bakersfield Dept Comp Sci Bakersfield CA 93311 USA

ISBN: (纸本)9781424407897

A mission of chemical plume tracing (CPT) in near-shore and ocean environments is to navigate an autonomous underwater vehicle (AUV) to find a chemical plume, to trace the plume to its source, and to declare the source location. It is necessary to recognize the declared odor source by using a visual system. Color images, which were taken in near-shore ocean environments when the source was declared, are very vague due to dim illumination conditions and fluid advection effects. This paper presents an iterative fuzzy segmentation (IFS) algorithm for extracting color components of the chemical plume and the odor source for visual confirmation of the correct declared odor source. The proposed approach might be of general interest in image processing and computer vision.

关键词： autonomous underwater vehicles chemical plume tracing fuzzy image segmentation odor source recognition

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Analysis and visualization of complex phenomena 16

Analysis and visualization of complex phenomena

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16th ieee International symposium on computational intelligence and Informatics, CINTI 2015

作者： Machado, J. A. Tenreiro Lopes, Antonio M. Institute of Engineering Polytechnic of Porto Dept. of Electrical Engineering R. Dr. António Bernardino de Almeida 431 Porto4249-01 Portugal UISPA-LAETA/INEGI Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal

ISBN: (纸本)9781467385206

In this paper we study natural and man-made complex phenomena by means of signal processing and fractional calculus. The outputs of the complex phenomena are time series to be interpreted as manifestations of the system dynamics. In a first step we use the Jensen-Shannon divergence to compare real-world signals. We then adopt multidimensional scaling and visualization tools for data clustering and analysis. Classical and generalized (fractional) Jensen-Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand distinct phenomena. © 2015 ieee.

关键词： signal processing

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Fast multi-spectral image coding algorithm based on fractal

Fast multi-spectral image coding algorithm based on fractal

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International symposium on intelligence Information processing and Trusted Computing

作者： Zhu, Lei Yang, Jing College of Automation Chongqing University Chongqing 400044 China Karamay Institute of Technology Xinjiang 833600 China

ISBN: (纸本)9780769541969

It is need to carry on the compression to the remote sensing image for the speedy transmission and the effective memory remote sensing image. The multi-spectrum remote sensing image has the very strong relevance among spectrums. In multi-wave band image compression, to eliminate the spectrum relevance, both must consider to eliminate the statistical dependence, and to eliminate the structure relevance. According to the multi-wave band remote sensing image's characteristic, this article proposed that one kind of four fork tree piecemeal, the match information pre-stores and first searches the match the fast fractal encoding method. Proved through algorithm realization and the experiment, this article proposed the method to enhance multi-spectrum remote sensing image the compression ratio, the reduction time of compression to have certain function. © 2010 ieee.

关键词： Fractals

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An assessment of Tikhonov regularizations to evoked brain signals

An assessment of Tikhonov regularizations to evoked brain si...

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5th International symposium on image and signal processing and Analysis

作者： Aydin, Serap Ondokuz Mayis Univ EEE Dept Samsun Turkey

ISBN: (纸本)9789531841160

The current work address two types of Tikhonov Regularization to extracta template evoked potential (EP) signal from a small number of noisy records. Under the same goal, the Subspace Regularization Technique (SRT) was experienced in literature without comparison regarding as the standard form Tikhonov Regularization technique (STRT). Both methods are tested in experimental studies and simulations. The signal-to-Noise Ratio (SNR) improvement is used as error criteria. The superiority of SRT have not been observed in results. In addition, the STRT is found to be less computational complex. The STRT method is optimum for smooth solutions whereas the SRT allows sharp variations in the solutions. Thus, we propose the use of the STRT instead of the SRM for template auditory EP estimation.

关键词： signal to noise ratio

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Application of Simulated Annealing Algorithm in Pest image Segmentation

Application of Simulated Annealing Algorithm in Pest Image S...

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2nd International symposium on computational intelligence and Design

作者： Mou, Yi Zhao, Qing Zhou, Long Anhui Sci & Technol Univ Dept Engn Fengyang Anhui Peoples R China Wuhan Polytech Univ Ind & Commercial Coll Dept Informat Engn Wuhan Peoples R China

ISBN: (纸本)9780769538655

Traditional pest detection methods can't provide the grain pests' categories, densities and other parameters. In addition, with the increase of the stored-grain pests' drug fastness, their categories and densities are increasing in recent years, With the development of pattern recognition, image processing, intelligent algorithm, computer technology, develop a new detection system is necessary and imperious. image segmentation is a key step in this system. In this paper, the basis of image segmentation is introduced;the improved fuzzy C-means clustering based on simulated annealing algorithm is applied to the stored-grain image segmentation. The Mat lab simulation experiments demonstrate that this method is more effective than fuzzy C-means clustering and classic segmentation algorithm, and it can segment the pest image better.

关键词： image segmentation stored-grain pest image simulated annealing algorithm fuzzy C-means clustering

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Efficient Foreground Extraction From HEVC Compressed Video for Application to Real-Time Analysis of Surveillance 'Big' Data

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ieee TRANSACTIONS ON image processing 2015年第11期24卷 3574-3585页

作者： Dey, Bhaskar Kundu, Malay K. Indian Stat Inst Ctr Soft Comp Res Kolkata 700108 India Indian Stat Inst Machine Intelligence Unit Kolkata 700108 India

While surveillance video is the biggest source of unstructured Big Data today, the emergence of high-efficiency video coding (HEVC) standard is poised to have a huge role in lowering the costs associated with transmission and storage. Among the benefits of HEVC over the legacy MPEG-4 Advanced Video Coding (AVC), is a staggering 40 percent or more bitrate reduction at the same visual quality. Given the bandwidth limitations, video data are compressed essentially by removing spatial and temporal correlations that exist in its uncompressed form. This causes compressed data, which are already de-correlated, to serve as a vital resource for machine learning with significantly fewer samples for training. In this paper, an efficient approach to foreground extraction/segmentation is proposed using novel spatio-temporal de-correlated block features extracted directly from the HEVC compressed video. Most related techniques, in contrast, work on uncompressed images claiming significant storage and computational resources not only for the decoding process prior to initialization but also for the feature selection/extraction and background modeling stage following it. The proposed approach has been qualitatively and quantitatively evaluated against several other state-of-the-art methods.

关键词： Background subtraction HEVC statistical signal processing video surveillance transform coding

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SUPERVISED LEARNING FOR SEGMENTING OPEN BOUNDARIES IN MEDICAL imageS 17

SUPERVISED LEARNING FOR SEGMENTING OPEN BOUNDARIES IN MEDICA...

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ieee 17th International symposium on Biomedical Imaging (ISBI)

作者： Amer, Karim Jacob, Athira Funka-Lea, Gareth El-Zehiry, Noha Siemens Healthineers Princeton NJ 08542 USA

ISBN: (数字)9781538693308

ISBN: (纸本)9781538693308

image segmentation is one of the most important building blocks in many medical imaging applications. Often, it is the first step in any artificial intelligence (AI) assisted diagnosis system. Most convolutional neural network image-to-image segmentation algorithms compute a binary mask segmentation and extract the object boundary as the edge of the binary mask always leading to a closed boundary. In this paper, we present a novel image-to-image segmentation algorithm that learns open boundaries. The object delineation is directly learnt by training a U-Net like network on a distance map representation of the boundary without any constraints on its shape or topology. We validate the proposed approach on the segmentation of the left atrium in intra-cardiac echocardiography images. For this application, it is important to produce segmentations only where a strong evidence of the anatomy exists. To our knowledge, this is the first work to train a U-Net on a distance map ground truth representation for open boundary segmentation.

关键词： image segmentation Training Ice Biomedical imaging image edge detection computational modeling Prediction algorithms

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