TENCON 2008 - 2008 IEEE Region 10 Conference最新文献_第8页

Fingerprint matching using transform features 基于变换特征的指纹匹配

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766494

M. Dale, M. Joshi

{"title":"Fingerprint matching using transform features","authors":"M. Dale, M. Joshi","doi":"10.1109/TENCON.2008.4766494","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766494","url":null,"abstract":"In the fingerprint recognition application utilizing more information other than minutiae is much helpful. We present here a fingerprint matching scheme based on transform features and their comparison. The technique described here obviates the need for extracting minutiae points to match fingerprint images. The proposed scheme uses Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) to create feature vector for fingerprints. After finding out the core point, fingerprint image of size 64times64 is cropped around the core point. The transform is applied on the cropped image without any pre-processing. The transform coefficients are arranged in specific manner and are used to obtain the feature vector in terms of standard deviation. The fingerprint matching is based on the minimum Euclidean distance between two feature vectors. Here database is formed by capturing 8 images per person using 500 dpi optical scanner. Training images used to form feature vector are 2, 4 or 6 per person. In the matching phase either all or remaining images are checked in identification mode to find out the percentage recognition rate. Comparison for all the three transform is presented here and it is observed that DCT and DFT gives better result as compared DWT.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89280810","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}

引用次数: 16

Model reference linear adaptive control of DC motor using fuzzy controller 基于模糊控制器的直流电动机模型参考线性自适应控制

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766484

A. Suresh kumar, M. Subba Rao, Y. Babu

引用次数: 19

Improving multi-objective clustering through support vector machine: Application to gene expression data 支持向量机改进多目标聚类:在基因表达数据中的应用

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766630

A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay

引用次数: 1

Validation of PCA and LDA for SAR ATR PCA和LDA在SAR ATR中的应用验证

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766807

A. Mishra

{"title":"Validation of PCA and LDA for SAR ATR","authors":"A. Mishra","doi":"10.1109/TENCON.2008.4766807","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766807","url":null,"abstract":"Both principal component analysis (PCA) and linear discriminant analysis (LDA) have long been recognized as tools for feature extraction and data analysis. There has been reports in the open literature regarding the performance of both LDA and PCA as feature extractors in various types of classification and recognition problems. Many of the reports claim a better performance with LDA than with PCA. However, the grounds of comparison have mostly been quite narrow. In the current paper PCA and LDA based classifiers are evaluated for the problem of synthetic aperture radar based automatic target recognition problem. The results show that in terms of absolute performance, PCA outperforms LDA. Results of PCA based classifier are also found to be of higher confidence than those from LDA based classifiers, as observed from the error-bar analysis of the classifiers.With decreased amount of training dataset, the degradation in the performance of the classifiers are almost similar in nature. The current work concludes that LDA is not suitable for radar image based target recognition task. This is in line with reports from some works in the open literature which claim that the success of LDA will depend on the type of data and whether there is exhaustive data available during the training phase or not.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89944257","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}

引用次数: 110

Improved performance irregular quasi-cyclic LDPC code design from BIBD’s using threshold minimization 利用阈值最小化改进了不规则准循环LDPC码设计的性能

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766569

S.R. Patil, S. Pathak

引用次数: 1

Fuzzy techniques and hierarchical aggregation functions decision trees for the classification of epilepsy risk levels from EEG signals 基于模糊技术和层次聚合函数决策树的脑电信号癫痫危险等级分类

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766545

R. Sukanesh, R. Harikumar

{"title":"Fuzzy techniques and hierarchical aggregation functions decision trees for the classification of epilepsy risk levels from EEG signals","authors":"R. Sukanesh, R. Harikumar","doi":"10.1109/TENCON.2008.4766545","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766545","url":null,"abstract":"The purpose of this paper is to identify the practicability of hierarchical soft (max-min) decision trees in optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical soft decision tree (post classifier with max-min criteria) four types are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patientpsilas risk level. The efficacy of the above methods is compared based on the bench mark parameters such as performance index (PI), and quality value (QV). A group of ten patients with known epilepsy findings are used for this study. High PI such as 95.88 % was obtained at QVpsilas of 22.43 in the hierarchical decision tree optimization when compared to the value of 40% and 6.25 through fuzzy classifier respectively. It is identified the hierarchical soft decision tree (Hier & h min-max) method is a good post classifier.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87910081","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}

引用次数: 7

A low complexity demodulator for coordinate interleaved modulation schemes 一种用于坐标交错调制方案的低复杂度解调器

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766432

G.A. Srinivas, D.N. Rohith, M. Z. Ali Khan

引用次数: 0

An approach to reversible information hiding for images 一种图像可逆信息隐藏方法

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766672

S. Arjun, N. Rao

{"title":"An approach to reversible information hiding for images","authors":"S. Arjun, N. Rao","doi":"10.1109/TENCON.2008.4766672","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766672","url":null,"abstract":"Information hiding (also known as data hiding), is a process of embedding secret message into a cover media for the purpose of covert communication, identification, security and copyright. Information hiding is used to conceal the content of messages. This is achieved by hiding secret message into other digital media like audio, images, video etc. For hiding secret message information in images, there exists a large variety of techniques, of which most techniques cause distortions in the original image even after secret message recovery, either due to bit-replacement or quantization error or truncation. It is especially important for medical and military applications that the image obtained after data extraction should be distortion free. Reversible data-hiding is the technique which embeds data in to a digital media such that the original media can be recovered without any distortion after the hidden message has been extracted. In this paper we propose a lossless method which embeds and extracts the data in the spatial domain. This method uses only one statistic parameter which controls the embedding and extraction of data. Two methods with different block orientations have been proposed. The novel method allows for an increase of 41.57% in average embedding efficiency when compared to existing methods, while maintaining the cover image degradation (PSNR - peak signal to noise ratio) at a comparable level. We also suggest a multi-layered embedding for increasing embedding capacity further.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88979852","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}

引用次数: 5

Analysis of center of pressure signals using Empirical Mode Decomposition and Fourier-Bessel expansion 用经验模态分解和傅里叶-贝塞尔展开分析压力信号中心

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766596

R. B. Pachori, D. Hewson, H. Snoussi, J. Duchêne

引用次数: 25

Improved representation of power system load dynamics using heuristic models 利用启发式模型改进电力系统负荷动态表示

TENCON 2008 - 2008 IEEE Region 10 Conference Pub Date : 2008-11-01 DOI: 10.1109/TENCON.2008.4766550

S. Halwi, D. G. Holmes, T. Czaszejko, M.B. Khoorasani

{"title":"Improved representation of power system load dynamics using heuristic models","authors":"S. Halwi, D. G. Holmes, T. Czaszejko, M.B. Khoorasani","doi":"10.1109/TENCON.2008.4766550","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766550","url":null,"abstract":"The importance of having accurate load models in power system stability studies has been well established in the literature as being essential for precise power system transient event investigations. The power industry presently uses composite load models in typical stability programs (e.g. LOADSYN and PSS/E). However, the parameters of the composite load models need to be tuned for each type of disturbance based on an assumed load composition, and are often inadequate for matching the modeled dynamics of the power system disturbance event to actual measured results. A stochastic time series technique in the form of an ARMAX mathematical model is presented in this paper as a novel alternative for dynamic load modeling. The model parameters are estimated using on-line measurement data for a number of disturbance events, collected from five substations in the Victorian electricity network in Australia. The performance of the model is then evaluated for other transient events, and compared against the recorded response for these events. The results achieved show that this heuristic-based model is robust and effective in predicting the dynamic response of a power system load across a range of events spanning various seasons and locations.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76462983","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}

引用次数: 0