2006 Fourth International Conference on Intelligent Sensing and Information Processing最新文献_第4页

Wavelet-Threshold based ECG Compression with Smooth Retrieved Quality for Telecardiology 基于小波阈值的心电信号平滑压缩

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286079

M. Manikandan, S. Dandapat

引用次数: 9

Evolving GA Classifiler for Audio Steganalysis based on Audio Quality Metrics 基于音频质量度量的音频隐写分析进化GA分类器

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286072

S. Geetha, S.S. Sivatha Sindhu, S. Gobi, A. Kannan

{"title":"Evolving GA Classifiler for Audio Steganalysis based on Audio Quality Metrics","authors":"S. Geetha, S.S. Sivatha Sindhu, S. Gobi, A. Kannan","doi":"10.1109/ICISIP.2006.4286072","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286072","url":null,"abstract":"Differentiating anomalous audio document (Stego audio) from pure audio document (cover audio) is difficult and tedious. Steganalytic techniques strive to detect whether an audio contains a hidden message or not. This paper presents a genetic algorithm (GA) based approach to audio steganalysis, and the software implementation of the approach. The basic idea is that, the various audio quality metrics calculated on cover audio signals and on stego-audio signals vis-a-vis their denoised versions, are statistically different. GA is employed to derive a set of classification rules from audio data using these audio quality metrics, and fitness function is used to judge the quality of each rule. The generated rules are then used to detect or classify the audio documents in a real-time environment. Unlike most existing GA-based approaches, because of the simple representation of rules and the effective fitness function, the proposed method is easier to implement while providing the flexibility to generally detect any new steganography technique. The implementation of the GA based audio steganalyzer relies on the choice of these audio quality metrics and the construction of a two-class classifier, which will discriminate between the adulterated and the untouched audio samples. Experimental results show that the proposed technique provides promising detection rates.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605157","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: 4

An Adaptive Fractional Pixel Search Algorithm 一种自适应分数像素搜索算法

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286084

Liquan Shen, Zhaoyang Zhang, Zhi Liu, Wenjun Zhang

引用次数: 3

Sensor-Based Fast Thermal Evaluation Model For Energy Efficient High-Performance Datacenters 基于传感器的高效节能高性能数据中心快速热评估模型

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286097

Qinghui Tang, T. Mukherjee, S. Gupta, Phil Cayton

引用次数: 219

Updating Student Model using Bayesian Network and Item Response Theory 利用贝叶斯网络和项目反应理论更新学生模型

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286086

Yaser Nouh, P. Karthikeyani, Dr. R. Nadarajan

引用次数: 3

Document Page Layout Analysis Using Harris Corner Points 使用哈里斯角点分析文档页面布局

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286083

F. Nourbakhsh, P. Pati, A. Ramakrishnan

引用次数: 7

A Distributed Approach to Hyper-Spectral Image Analysis Using Support Vectors 基于支持向量的分布式高光谱图像分析方法

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286085

S. Sindhumol, M. Wilscy

{"title":"A Distributed Approach to Hyper-Spectral Image Analysis Using Support Vectors","authors":"S. Sindhumol, M. Wilscy","doi":"10.1109/ICISIP.2006.4286085","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286085","url":null,"abstract":"This paper presents a detailed analysis of a new distributed algorithm designed for hyper-spectral image analysis. Hyper-spectral imaging is a valuable technique for detection and classification of materials and objects on the Earth's surface. The conventional approach to hyper-spectral image analysis is based on dimensionality reduction using Principal Component Analysis (PCA). But the results contain more details of the frequently occurred objects compared to the minor objects in the scene. To resolve this, a new algorithm for hyper-spectral image analysis based on Support Vector Clustering (SVC) and Spectral Angle Mapping (SAM) is proposed in this work. The method is found to generate good results, but the calculation of Support Vectors, Spectral Angles and Principal Components are very time-consuming processes and a bulk of data is to be processed to analyse the hyper-spectral images. So the algorithm is designed in a distributed manner and a distributed environment based on Java/RMI is developed to implement it. The algorithm is tested with two Hyper-spectral image datasets of 210 bands each, which are taken with HYper-spectral Digital Imagery Collection Experiment (HYDICE) air-borne sensors. A performance analysis of the distributed environment is also carried out.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129971681","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

Security for Pervasive Health Monitoring Sensor Applications 普及健康监测传感器应用的安全性

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286096

K. Venkatasubramanian, S.K.S. Gupta

引用次数: 93

A natural number based linear time filtering approach to finding all occurrences of a DNA pattern 一种基于自然数的线性时间滤波方法，用于发现DNA模式的所有出现

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286078

V. Le

引用次数: 2

A Minimal Protocol for Authenticated Key Distribution in Wireless Sensor Networks 无线传感器网络中认证密钥分配的最小协议

2006 Fourth International Conference on Intelligent Sensing and Information Processing Pub Date : 2006-12-01 DOI: 10.1109/ICISIP.2006.4286066

K. Singh, V. Muthukkumarasamy

引用次数: 7