{"title":"Bidimensional Empirical Mode Decomposition for multiresolution image coding","authors":"C. Guaragnella, A. Manni, F. Palumbo, T. Politi","doi":"10.1109/CIMSA.2010.5611762","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611762","url":null,"abstract":"Bidimensional Empirical Mode Decomposition (BEMD) provides a tool for image processing for its special ability to locally separate spatial frequencies. The Intrinsic Mode Functions (IMFs) other than the first are images of lower frequency components. The coding method presented in this paper uses the BEMD process to create two sub-band images from the original image: hi and low frequency. These images are differently subsampled and compressed by JPEG standard with different quality factor and then sent to a feedback system to compensate the quality loss in the compression process. The proposed paper proposes a technique to enhance jpeg encoding of images. Reconstructed images produce increased visual appearance of correspondent jpeg coded ones at same compression rate.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498733","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":"Self-descriptive IF THEN rules from signal measurements: A holonic-based computational technique","authors":"M. Calabrese","doi":"10.1109/CIMSA.2010.5611760","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611760","url":null,"abstract":"A holon is a bio-inspired conceptual entity that, like cells in a living organism, behaves as a part and a whole at the same time. Holonic systems have been the subject of intense research in the latest years due to their properties such as self-organization, self-similarity and capability of handling hierarchically-nested granularity levels. Lesser attention indeed has been paid by engineers to the aspect of self-description, i. e. the ability to describe itself in terms of self-contained descriptors. Self-description can be useful in measurement settings where the only available knowledge is embedded in data in terms of hidden rules behind observed signals. In this work, a heuristic technique is employed to extract self-descriptive IF THEN rules from measurement signals. These rules are considered holonic in that they represent a whole described in terms of relationships among their parts. An example taken from a real measurement scenario is reported and commented in detail.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116342158","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}
G. De Nunzio, M. Donativi, G. Pastore, L. Bello, R. Soffietti, A. Falini, A. Castellano
{"title":"Automatic segmentation and therapy follow-up of cerebral glioma in diffusion-tensor images","authors":"G. De Nunzio, M. Donativi, G. Pastore, L. Bello, R. Soffietti, A. Falini, A. Castellano","doi":"10.1109/CIMSA.2010.5611767","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611767","url":null,"abstract":"Gliomas are the most common primary brain tumors, with a typical infiltrative growth pattern along white matter (WM) fibers. Diffusion Tensor Imaging (DTI) is sensitive to the directional diffusion of water along WM tracts, which allows the identification of subtle peritumoral glioma infiltration that are not apparent on conventional Magnetic Resonance imaging. The aim of this study was to characterize pathological and healthy tissue in DTI datasets by statistical texture analysis, developing a Computer Assisted Detection (CAD) technique for cerebral glioma. This system, coupled to voxel-based tumor evolution analysis, could allow objective tumor identification and qualitative and quantitative measurements in the follow-up of patients during chemotherapy. In this paper, preliminary results of tumor segmentation and evolution analysis are shown.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125903295","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":"Incremental PCA-LDA algorithm","authors":"I. Dagher","doi":"10.1109/CIMSA.2010.5611752","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611752","url":null,"abstract":"In this paper a recursive algorithm of calculating the discriminant features of the PCA-LDA procedure is introduced. This algorithm computes the principal components of a sequence of vectors incrementally without estimating the covariance matrix (so covariance-free) and at the same time computing the linear discriminant directions along which the classes are well separated. Two major techniques are used sequentially in a real time fashion in order to obtain the most efficient and linearly discriminative components. This procedure is done by merging the runs of two algorithms based on principal component analysis (PCA) and linear discriminant analysis (LDA) running sequentially. This algorithm is applied to face recognition problem. Simulation results on different databases showed high average success rate of this algorithm compared to PCA and LDA algorithms. The advantage of the incremental property of this algorithm compared to the batch PCA-LDA is also shown.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"1999 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128260832","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":"Measurement of the principal singular point in contact and contactless fingerprint images by using computational intelligence techniques","authors":"R. D. Labati, A. Genovese, V. Piuri, F. Scotti","doi":"10.1109/CIMSA.2010.5611769","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611769","url":null,"abstract":"Biometric systems identify individuals by comparison of the individual biometric traits, such as the fingerprint patterns. In the literature, many relevant methods are based on the localization of a reference “pivot” point of the fingerprint, called principal singular point (PSP). Most of the time, the PSP is selected from the list of the estimated singular points (SPs) that are identified by specific local patterns of the fingerprint ridges, called cores and deltas. The challenge is to provide an automatic method capable to select the same PSP from different images of the same fingertip. In this paper, we propose a technique that estimates the position of all the singular points by processing the global structure of the ridges and extracting a specific set of features. The selection of the reference point from the candidate list is then obtained by processing the extracted features with computational intelligence classification techniques. Experiments show that the method is accurate and it can be applied on contact and contact-less image types.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125110680","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":"Auction approach for management of a virtual classroom","authors":"V. Di Lecce, Alessandro Quarto, A. Giove","doi":"10.1109/CIMSA.2010.5611758","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611758","url":null,"abstract":"the goal of this study is to propose a virtual classroom tool integrated within an e-learning 2.0 architecture supported by a multi agent system with auction-based approach. The proposed architecture and related features aim to provide the teacher / tutor with functionalities for monitoring, planning courses or redesigning them if necessary. The main purpose was to design a Multi Agent System (MAS) structure working in synergy with the learning environment chosen in order to simplify the management of the whole on-line training process. Specific constraints for defining the rules of the auction approach have been adopted. The test results have shown that intelligent agent technology can be used to personalize the learning environment and as a consequence to improve eLearning effectiveness.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131188823","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":"A priori knowledge-based recognition and inspection in carbide insert production","authors":"R. Schmitt, Yu Cai, T. Aach","doi":"10.1109/CIMSA.2010.5611757","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611757","url":null,"abstract":"In processes of the production chain of carbide inserts, such as unloading or packaging, the conformity test of the insert type is performed manually, which causes a statistic increase of errors due to monotony and fatigue of workers and the wide variety of insert types. A machine vision system is introduced that automatically measures and inspects the chip-former geometry of inserts, the most significant insert quality feature, in the production line. The proposed recognition approach is developed with utilisation of a priori knowledge of carbide inserts and of production environments. This new method has been tested on several inserts of different types. Test results show that prevalent insert types can be inspected and robustly classified in a real production environment and therefore the manufacturing automation can be improved.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134521831","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}
Hanif Tahersima, Fatemeh Tahersima, A. Mesgari, Mohammad Jafar, K. Saleh
{"title":"Prediction of Lorenz chaotic time series via Genetic Algorithm","authors":"Hanif Tahersima, Fatemeh Tahersima, A. Mesgari, Mohammad Jafar, K. Saleh","doi":"10.1109/CIMSA.2010.5611750","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611750","url":null,"abstract":"In this paper a method for time series prediction of chaotic systems is developed in order to increase the time horizon of prediction. Also it is assumed that the type of chaotic time series is known. In this investigation, the parameters of the chaotic system are estimated by minimizing the summation of absolute value of errors using Genetic Algorithm (GA). The results show that it is impossible to estimate accurate value of parameters because of high sensitivity of system parameters. However, it is shown that it is possible to have a model with different parameters but with similar behavior. The performance of the proposed method is investigated on Lorenz chaotic time series. The results demonstrate that the proposed method can considerably improve the horizon of prediction.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115441837","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}
B. Solomon, D. Ionescu, Marin Litoiu, Gabriel Iszlai, O. Proștean
{"title":"Measurements and identification of Autonomic Computing processes","authors":"B. Solomon, D. Ionescu, Marin Litoiu, Gabriel Iszlai, O. Proștean","doi":"10.1109/CIMSA.2010.5611771","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611771","url":null,"abstract":"There is a growing need for the automation of the IT infrastructure of enterprises. Autonomic computing provided a theoretical support for the foundation of mechanisms for self-optimization of computational resources at all the levels of the IT infrastructure of the enterprise. As the Autonomic Computing paradigm requires collecting information in regards to specific parameters based on which a decision module will act, the architecture of an autonomic computing system is very much similar to a real-time control system. Thus the validation of the model used for the mathematical characterization of the autonomic computing processes is crucial. In this paper, starting from the model of autonomic computing processes an identification technique adapted to autonomic computing processe, is introduced. The identification is based on injecting pseudo random arrival rates into the autonomic system as disturbances. The observations are collected from sensors for CPU load, throughput, response time, etc implemented in the middleware over which applications were deployed. The identification process described in this paper determines first the sampling rate and then uses the Recursive Parameter Estimation technique (RPE)for Extended Kalman Filters, to obtain a model on which the whole control strategy relies upon. Experiments and results are described in the end of this paper.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963377","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":"Computational-based volatile organic compounds discrimination: An experimental low-cost setup","authors":"V. Di Lecce, M. Calabrese, R. Dario","doi":"10.1109/CIMSA.2010.5611763","DOIUrl":"https://doi.org/10.1109/CIMSA.2010.5611763","url":null,"abstract":"In this work, an array of low-cost cross-sensitive sensors is used for discriminating the best candidate within a set of volatile organic compounds (VOCs). The challenge of our experimental setting is to deal with the problems of low selectivity, especially in normal operating conditions, so that ambiguous sensor responses (i.e. referable to more than one VOC) can be given, at least, a qualitative interpretation. In order to carry out the signal disambiguation task, a computational technique employing simple classifying rules and fuzzy descriptions has been engineered. The basic idea is that, if the same gas is actually measured by two or more sensors, then the estimated concentrations will show a low variance, with an accuracy related to the number of concordant sensors. Experiments show that, despite the cheapness of the setup and the coarse-grained nature of the provided response, encouraging results can be obtained and prospective work can follow.","PeriodicalId":162890,"journal":{"name":"2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131407435","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}