Much recent research is concerned with overcoming limitations of existing video surveillance systems, particularly for use in automatic human tracking systems. This paper presents detection methods which detect a lost...
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On-chip inductive effects are becoming predominant in deep submicron (DSM) interconnects due to increasing clock speed, circuit complexity and decreasing interconnect lengths. Inductance causes noise in the signal wav...
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In this paper the code marking and reading system is discussed that was created for tracing logs as a part of the EU 6(th) Framework project Indisputable Key. A set of images of codes on logs was acquired in SK Rolpin...
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ISBN:
(纸本)9789985599822
In this paper the code marking and reading system is discussed that was created for tracing logs as a part of the EU 6(th) Framework project Indisputable Key. A set of images of codes on logs was acquired in SK Rolpin (SKRP) sawmill in France and an automatic code reading software was developed and initial readability analysis was performed. Machine vision and decoding algorithms were developed and implemented. Code reading algorithm consists mainly of four distinct steps: image preprocessing, image orientation and compression, particle analysis and decoding of the code. This marking and decoding system was created to prove of values that can be gained thorough marking individual logs in sawmill. In parallel two different log code marking schemes were used and compared. Efficiency analysis of the imageprocessing algorithm reveals clear advantages of distinct and application specific algorithms which are analyzed and demonstrated in the paper. In spite of efficiency of the algorithm there exist several methods to increase artificially code contrast and visibility in different conditions. One of code visibility enhancing methods is using externally activated paints for code marks, especially infrared or ultraviolet light activated inks. Performance of this kind of markings is analyzed. Respective code marks are applied to logs and readability is tested. The test results are discussed in this paper and future directions for high effective code marking are given.
image inpainting is an interpolation problem where an image with missing or damaged parts is restored. The most often used image inpainting applications are for pictures or films known or damaged partially. Discarding...
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ISBN:
(纸本)9789604741939
image inpainting is an interpolation problem where an image with missing or damaged parts is restored. The most often used image inpainting applications are for pictures or films known or damaged partially. Discarding some unwanted parts, text or objects from the whole image space, special effects can be carried out using image restoration. Complex mathematical models based on partial differential equations (PDE) or variational computing was proposed as techniques for restoring damaged or partially known images. Those methods are computational expensive and difficult to implement, even when a large serial processing computing power is available. The Cellular Neural Networks (CNN) based parallelprocessing ensures computing-time reduction if the processing algorithm can be implemented on a continuous-time analogue CNN-UM (Cellular Neural/Nonlinear Networks Universal Machine) or using FPGA (Field Programmable Gate Array) implemented emulated digital CNN-UM. Even if variational computing methods are used, the design of CNN templates ensuring the desired processing of the gray-scale image remains an important step. In the present paper, some variational based CNN methods are presented and analyzed that can be used for the reconstruction of damaged or partially known images. Efficiency of these impanting methods can be enhanced by combining them with nonlinear template that ensures the growth of the local properties spreading area along with regional ones.
CUDA(Compute Unified Device Architecture) acceleration of very large scale matrix-vector and matrix-matrix multiplication is presented in this paper. The intrinsic parallelism in the matrix computations are exploited ...
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Extraction of frequent patterns from a transactional database is a fundamental task in data mining. Its applications include association rules, time series, etc. The Apriori approach is a commonly used generate-and-te...
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The proceedings contain 94 papers. The topics discussed include: indexing of compressed video: methods, challenges, applications;multidimensional particle swarm optimization and applications in data clustering and ima...
ISBN:
(纸本)9781424472482
The proceedings contain 94 papers. The topics discussed include: indexing of compressed video: methods, challenges, applications;multidimensional particle swarm optimization and applications in data clustering and image retrieval;distributed video coding: status, challenges and outlook;augmented reality: issues, trends and challenges;fusion and classification of multi-source images by SVM with selected features in a kernel space;feature subspaces selection via one-class SVM: application to textured image segmentation;adaptive feature selection for heterogeneous image databases;comparison of feature selection schemes for color texture classification;connectivity feature extraction for spatio-functional clustering of fMRI data;audio-video surveillance system for public transportation;people re-identification by classification of silhouettes based on sparse representation;and a benchmark for background subtraction algorithms in monocular vision: a comparative study.
Data security techniques based on optical theories and methods have been proposed and widely developed in recent years. Compared with conventional mathematical encryption methods optical security system provides highe...
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ISBN:
(纸本)9780819483812
Data security techniques based on optical theories and methods have been proposed and widely developed in recent years. Compared with conventional mathematical encryption methods optical security system provides higher processing speed, more information volume, more encryption free-degree as well as its multi-dimension and parallelprocessing abilities. In this paper we proposed a novel architecture for optical image encryption with polarization-selective diffractive optical element (PDOE) based on interference theory. A target image is firstly encoded into two phase-only distributions and then these phase distributions are encrypted into the etched surface-relief pattern of a single PDOE mask. In the process of optical image decryption, when the working wavelength and the system configuration are correct, the PDOE mask with the encoded information for the target image can generate two desired polarized wavefronts by modulating the incident light beam. These two wavefronts interfere and then generate the decrypted image. The encoding algorithm to generate the phase-only distributions is simple and it does not need iterative process. The optical realization for image decryption also has the advantages of easier installation and collimation since all the optical elements are in a same optical axis. The employment of the PDOE mask in this optical security system will highly increase the information security and still maintain the parameter sensitivity in an acceptable region. Numerical simulation is performed to demonstrate the validity of this new proposed method.
In this paper, we address the problem of unmixing hyperspectral images in a semi-supervised framework using the normal compositional model recently introduced by Eismann and Stein. Each pixel of the image is modeled a...
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ISBN:
(纸本)9781424442966
In this paper, we address the problem of unmixing hyperspectral images in a semi-supervised framework using the normal compositional model recently introduced by Eismann and Stein. Each pixel of the image is modeled as a linear combination of random endmembers. More precisely, endmembers are modeled as Gaussian vectors whose means belong to a known spectral library. This paper proposes to estimate the number of endmembers involved in the mixture, as well as the mixture coefficients (referred to as abundances) using a trans-dimensional algorithm. Appropriate prior distributions are assigned to the abundance vector (to satisfy constraints inherent to hyperspectral imagery), the noise variance and the number of components involved in the mixture model. The computational complexity of the resulting posterior distribution is alleviated by constructing an hybrid Gibbs algorithm which generates samples distributed according to this posterior distribution. As the number of endmembers is unknown, the sampler has to jump between spaces of different dimensions. This is achieved by a reversible jump Markov chain Monte Carlo method that allows one to handle the model order selection problem. The performance of the proposed methodology is evaluated thanks to simulations conducted on synthetic data.
Crustal movement modeling and analysis is one of the major tasks in the earth system science. In this paper, a distributed system for simulating the crustal movement was developed. The crustal movement simulation syst...
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