2011 IEEE 7th International Symposium on Intelligent Signal Processing最新文献

{"title":"A new tool for comparison and evaluation of medical images","authors":"L. Gráfová, J. Horejš, A. Procházka, M. Kasparová, T. Dostálová","doi":"10.1109/PSES.2011.6088252","DOIUrl":"https://doi.org/10.1109/PSES.2011.6088252","url":null,"abstract":"A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomograms taken before and after treatment. The accuracy of the performance has been discussed and the possible origins of tool performance errors have been explained. The results obtained using presented tool have been discussed by an expert. The expert has confirmed that the tool is well suited for comparison and evaluation of ortopantomograms. The expert has come to the conclusion that our tool can be useful in other specializations of dentistry, not only in orthodontics.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127512371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image inpainting using sparse approximation with adaptive window selection","authors":"S. K. Sahoo, Wenmiao Lu","doi":"10.1109/WISP.2011.6051703","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051703","url":null,"abstract":"In this paper the problem of image inpainting is addressed using sparse approximation of local image patches. The small patches are extracted by sliding square windows. An adaptive window selection procedure for local sparse approximation is proposed, which affects the global recovery of underlying image. Ideally the adaptive window selection yields the minimum mean square error (MMSE) in a recovered image. This framework gives us a clustered image based on the selected window size, each cluster is then inpainted separately using sparse approximation. The results obtained using the proposed framework are comparable with the recently proposed inpainting techniques based on sparse representation.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127355111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variable-resolution image processing for validation of coins","authors":"O. Martens, T. Saar, A. Gavrijaseva, A. Molder","doi":"10.1109/WISP.2011.6051711","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051711","url":null,"abstract":"In this paper correlation-based matching solutions of images for the case of the validation of the eurocoins with relatively high-speed motion have been developed and evaluated. Image processing (combined with other — electromagnetic, optical and acoustical sensorics) is an efficient method for coin recognition and validation. From the image processing viewpoint — an universal method is finding and checking the coin image by cross-correlating it with expected (reference) image(s). Correlation is widely used as an effective similarity measure in matching tasks. However, traditional correlation based matching methods are limited by various ways. Main challenge here (additionally to \"pre-conditioning\" of compared images, of course) is the significant reduction of the computations, needed for finding cross-correlation values over 2-D space and for all possible rotation values. In current work usage of variable-rate subsampled (by pixel blocks) reference images has been proposed and evaluated. A special case has been considered, where most of the image blocks are sampled with zero (none) or one sample-values, while a few blocks (some to some tens) of the image has been sampled at the full accuracy (eg 240−240 pixels, in the used examples). The criteria, used for selection of the “specific” (unique) blocks of the reference image has been the minimum value of the maximum cross-correlation of an block of samples (eg 20−20 or 30−30 pixels) against any other (shifted or rotated) block of the same coin image. So, blocks with relatively high value of “secondary “correlation peaks at shifting and rotating are not considered as “good or unique” ones. So, sub-sampled reference images for various eurocoins has been proposed, and corresponding algorithms has been evaluated. Alternatively, using of set of feature-points of the images, as reference for cross-correlation, has been evaluated, for various eurocoins (with corresponding determination of reasonable feature points, for these coins). Alternatively, using local maximum and minimum difference based interesting pixel blocks as reference blocks for cross-correlation has been discussed. These methods have been tested on real eurocoins, the results are presented at the end of paper.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129105140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intellectual software for analysis of histological images","authors":"A. Nedzved, V. Starovoitov","doi":"10.1109/WISP.2011.6051704","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051704","url":null,"abstract":"A new solution to the analysis of histological images is presented. It is based on the intelligent software. The core of this software is an interpreter, which combines simple image processing functions. After analysis of image properties a script is generated for an interpreter. The script consists of a sequence of simple functions. Our methodology of a script construction is presented in the paper. A collection of scripts may be saved and used to solve various complex problems of histological image analysis.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123660086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chaos synchronization in Duffing systems with Robust Fixed Point Transformations","authors":"T. A. Várkonyi, J. Tar, I. Rudas","doi":"10.1109/WISP.2011.6051709","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051709","url":null,"abstract":"Nowadays Lyapunov's second method is the most prevailing solution in adaptive control problems. Despite of the idea being splendid, recently other solutions have come up which seem to be more beneficial in some cases. One of these methods is the family of Robust Fixed Point Transformations (RFPT) which proved to be effective in several areas, for example in Classical Mechanical Systems, Electromechanical Systems and in the frames of Model Reference Adaptive Controllers (MRAC). In this paper a novel application of RFTP, the synchronization of two chaotic Duffing systems is shown. Numerical simulations illustrate and confirm the usefulness of the procedure.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125796159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved back-propagation algorithm for neural network training","authors":"A. Várkonyi-Kóczy, B. Tusor","doi":"10.1109/WISP.2011.6051720","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051720","url":null,"abstract":"Recently, Artificial Neural Networks (ANNs) have become popular because they can learn complex mappings from the input/output data and are relatively easy to implement in any application. Although, a disadvantageous aspect of their usage is that they need (usually a significant amount of) time to be trained, which scales with the structural parameters of the networks and with the quantity of the input data. However, the training can be done offline; it has a non-negligible cost and further, can cause a delay in the operation. Fuzzy Neural Networks (FNNs) are the combinations of ANNs and fuzzy logic in order to incorporate the advantages of both methods (the learning ability of ANNs and the thinking ability of fuzzy logic). FNNs have fuzzy values in their weight parameters and in the output of each neuron. Circular Fuzzy Neural Networks (CFNNs) are FNNs with their topology realigned to a circular topology and the connections between the input layer and hidden layer trimmed. This may result in a dramatic reduction in the training time, while the precision and accuracy of the network are not affected. To further increase the speed of the training of the ANNs, FNNs, or CFNNs used for classification, a new training procedure is introduced in this paper: instead of directly using the training data in the training phase, the data is first clustered and the neural networks are trained by using only the centers of the obtained clusters.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133884553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of an intelligent sensor for measurement and prediction of solar radiation and atmospheric temperature","authors":"João M. Gomes, P. Ferreira, A. Ruano","doi":"10.1109/WISP.2011.6051713","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051713","url":null,"abstract":"The aim of this study was to develop an intelligent sensor for acquiring temperature, solar radiation data and estimate cloudiness indexes, and use these measured values to predict temperature and solar radiation in a close future. The prototype produced can ultimately be used in systems related to thermal comfort in buildings and to the efficient and intelligent use of solar energy. To incorporate these functionalities, a small and portable prototype was developed, which consisted in: a CCTV camera with a fish-eye lens, for sky images acquisition; a computer of format mini-itx with a Linux operative system, for data acquisition and processing; a GPS, to enable automatic use, independent of the system's geographical position; a pyranometer, for regular measurements of solar radiation; a temperature probe, for regular measurements of outdoor temperature; a shadow band, to eliminate the sun's flare effect on sky images; Arduino, an open source electronics prototyping platform that acquires data from the temperature and solar radiation sensors, as well as processing the data provided by the GPS and controlling the shadow band; neural networks of the type NARX, which use the acquired data to forecast the cloudiness index, solar radiation and temperature, in the next four hours period. The system was programmed to acquire data, both from the sensors and the camera, every five minutes.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132867784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wavelet-based sensor validation: Differentiating abrupt sensor faults from system dynamics","authors":"A. Kozionov, Mikhail Kalinkin, Alexey Natekin, Alexander Loginov","doi":"10.1109/WISP.2011.6051716","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051716","url":null,"abstract":"The problem of sensor fault detection is important part of the overall system health estimation. Without assuring correct sensor readings it is impossible to make any conclusion about system status. On the other hand, it is essential not to confuse sensor faults and abnormal sensor behavior caused by other reasons, such as dynamically changing system condition or fault in the system. In the current paper the problem of distinguishing between sensor faults and system dynamics is investigated. This problem cannot be solved by validating each sensor signal independently; it requires joint analysis of all sensors. The particular case of several redundant of well-correlated sensors is considered. The proposed solution consists of two steps. First, multiresolution analysis, a powerful wavelet-based signal processing technique, is applied to detect signal changes both at high and low frequency scales. Then, found changes are inspected on different wavelet detail levels and decision is made whether these changes are true sensor faults or are caused by system dynamics. The proposed method is tested on data from gas turbine power plant.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127285594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing time-frequency parameters estimation for Doppler Ultrasound blood-flow signals","authors":"B. Zabihian, M. Ruano","doi":"10.1109/WISP.2011.6051708","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051708","url":null,"abstract":"Doppler Ultrasound (DU) blood flow signals, particularly when collected under intra-operative conditions are noisy; accurate extraction of clinical parameters from their spectra becomes a difficult task. The spectral center frequency and bandwidth were estimated using two estimators with alternative time-frequency resolutions: a fixed resolution method, the Short-Time Fourier Transform (STFT) and the multi-resolution Continuous Wavelet Transform (CWT). Their performance was also assessed when the DU signals were pre-processed by a recently proposed Noise Cancellation Technique (NCTech). The NCTech algorithm enables quantification of the magnitude of the canceled noise in the form of percentage, called Cancellation Level (CL). Quantitative comparisons have been performed in terms of bias of the estimators when four signal-to-noise (SNRs) on DU simulated signals are employed: infinity, 20 dB, 10 dB and 5 dB. Results prove that CWT produced spectral parameters estimates with less bias than STFT; however these estimates were less consistent than the STFT ones. When NCTech is primarily applied to the signal, the STFT is the method to benefit most from this pre-processing technique. The CWT combined with NCTech produced estimates of both spectral parameters with better accuracy over the majority of the cardiac cycle, except where the frequency varies within a small range of frequencies during a short period of time.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125347471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a more analytical training of neural networks and neuro-fuzzy systems","authors":"A. Ruano, C. Cabrita, P. Ferreira","doi":"10.1109/WISP.2011.6051695","DOIUrl":"https://doi.org/10.1109/WISP.2011.6051695","url":null,"abstract":"When used for function approximation purposes, neural networks belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. In this work we extend this concept to the case where the training problem is formulated as the minimization of the integral of the squared error, along the input domain. With this approach, the gradient-based non-linear optimization algorithms require the computation of terms that are either dependent only on the model and the input domain, and terms which are the projection of the target function on the basis functions and on their derivatives with respect to the nonlinear parameters. These latter terms can be numerically computed with the data provided. The use of this functional approach brings at least two advantages in comparison with the standard training formulation: firstly, computational complexity savings, as some terms are independent on the size of the data and matrices inverses or pseudo-inverses are avoided; secondly, as the performance surface using this approach is closer to the one obtained with the true (typically unknown) function, the use of gradient-based training algorithms has more chance to find models that produce a better fit to the underlying function.","PeriodicalId":223520,"journal":{"name":"2011 IEEE 7th International Symposium on Intelligent Signal Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122305034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}