{"title":"Soft Computing and Dynamic Tunneling Paradigms in Network Security Attacks","authors":"N. Nalini, R. Raghavendra","doi":"10.1109/ICISIP.2006.4286067","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286067","url":null,"abstract":"Most cryptanalysis problems are characterised by a feature having one global optimum solution and several local minima, when formulated as an optimisation problem. Among the several heuristic techniques adopted to solve such optimisation problems, it is noticed that a genetic algorithm gets trapped at a local minimum solution. Dynamic tunneling technique has been recently used for obtaining global optimum solution for several problems. Motivated by this fact, we adopt a hybrid version of genetic algorithm and dynamic tunneling technique for the cryptanalysis of a popular stream cipher SEAL (software encryption algorithm). The concepts developed in the paper are useful in the cryptanalysis of block and stream ciphers.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"20 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114029104","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 Simple Method to Design FIR QMF Banks","authors":"A. Ramakrishna, M. Nigam","doi":"10.1109/ICISIP.2006.4286103","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286103","url":null,"abstract":"An iterative method for the design of two-band quadrature mirror filter (QMF) banks proposed by Cruesere and Mitra is examined and improved by designing the prototype filters using window method instead of equiripple method. The Kaiser window and Chebyshev window functions are used in the design of prototype filters. The cut-off frequency has been adjusted in this improved method instead of passband frequency which is the case in Cruesere and Mitra algorithm. The paper concludes with design results and comparisons that show that our new improved method takes less computational effort when compared with Cruesere and Mitra method.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"13 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":"115345962","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":"An Efficient Track Management Scheme for the Gaussian-Mixture Probability Hypothesis Density Tracker","authors":"K. Panta, Ba-Ngu-Vo, D. Clark","doi":"10.1109/ICISIP.2006.4286102","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286102","url":null,"abstract":"The Gaussian mixture probability hypothesis density (GM-PHD) filter is a closed-form solution for the probability hypothesis density (PHD) filter, which was proposed for jointly estimating the time-varying number of targets and their states from a sequence of noisy measurement sets in the presence of data association uncertainty, clutter and miss-detections. Recently, a GM-PHD tracker based on the GM-PHD filter has been proposed to correctly maintain temporal association amongst target estimates by tagging individual Gaussian components, and to provide estimates of individual target trajectories and their identities. In this paper, we propose a tag and a track management scheme for the GM-PHD tracker, which is computationally efficient and provides a framework for parallel processing of data. Based on the proposed scheme, we also present a number of simpler and efficient pruning schemes for Gaussian components.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"37 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":"127590439","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":"An Audio Equalisation Linear Phase FIR Filter Design Method using RBF based Smoothing and Interpolation","authors":"A. Zaknich, G.E. Lee","doi":"10.1109/ICISIP.2006.4286073","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286073","url":null,"abstract":"A method for the design of audio equalisation linear phase FIR filters is developed by using a variant of the tuneable approximate piecewise linear regression (TAPLR) method to model the required FIR magnitude frequency response. This TAPLR model incorporates a set of contiguous piecewise linear (affine) sections which are coupled and smoothed by a single tuning parameter associated with a set of bandwidth weighted radial basis functions (RBFs) assigned to each linear section. The main difference between this variant and the original TAPLR method is that it incorporates RBFs with variable bandwidths that can be centred and set according to standard nonlinear frequency spacings as used for audio system response measurements, thereby producing a more accurate response model. The TAPLR smoothing mechanism is used to achieve the required degree of FIR filter band limiting to avoid aliasing effects and the Gibbs phenomenon. Some typical audio FIR filter design examples are provided to show the value and versatility of the method as compared with the standard windowing design approach.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"33 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":"130966742","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":"Linear Feature Extraction using combined approach of Hough transform, Eigen values and Raster scan Algorithms","authors":"J. Prakash, M. B. Meenavathi, K. Rajesh","doi":"10.1109/ICISIP.2006.4286063","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286063","url":null,"abstract":"In this paper we propose a new method for linear geometric primitive identification which uses the generalized standard Hough transform (HT), Eigen value based statistical parameter analysis and Bresenham 's raster scan algorithms. In this method, we use the sparse matrix to find the Hough transform of the given image. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage in matrix storage space and computational time. Hough peaks are identified based on neighborhood suppression scheme. After finding the meaningful and distinct Hough peaks, coordinates of linear features in Hough space can be obtained using Bresenham's raster scan algorithm. Since quantization in parameter space of the HT gives both the real and false primitives because of quantization in the space of digital image, quantization in parameter space of HT as well as the fact that the edges in typical images are not perfectly constitutes the geometrical features, a statistical analysis is done using the eigen values to characterize and identifying the geometrical primitives. The proposed method has the advantages of small storage, high speed, and accurate digitization of Hough space and less line extraction error ratio over previously presented HT based techniques and its invariants.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"2 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":"114153008","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":"Steganalysis of LSB Embedded Images Using Variable Threshold Color Pair Analysis","authors":"K. Raja, N. Shankara, K. Venugopal, L. Patnaik","doi":"10.1109/ICISIP.2006.4286051","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286051","url":null,"abstract":"Steganography and steganalysis are important areas of research in recent years involving a number of applications. Steganography is the science of embedding information into the cover image without causing statistically significant perturbations to the cover image. Steganalysis is the technology that attempts to defeat steganography by detecting the hidden information and extracting or destroying it. In this paper we present twenty four bits BMP image color pair analysis with variable threshold (CPAVT) to detect stego-object with 10% payload. In earlier works 20% payload was used in close color pair analysis. It is observed that with new variable threshold technique, the performance parameters, i.e. false detection rate (FDR) and false alarm rate (FAR) are better in comparison with the earlier works.","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":"129643737","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":"Binarization and Localization of Text Images Captured on a Mobile Phone Camera","authors":"B. Antony, P. Pati, A. Ramakrishnan","doi":"10.1109/ICISIP.2006.4286101","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286101","url":null,"abstract":"This paper proposes and compares four methods of binarizing text images captured using a camera mounted on a cell phone. The advantages and disadvantages (image clarity and computational complexity) of each method over the others are demonstrated through binarized results. The images are of VGA or lower resolution.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"40 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":"123356320","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}
K. Srinivasa, M. Jagadish, S. Prashanth, K. Venugopal, L. Patnaik
{"title":"Exploring Structurally Similar Protein Sequence Motifs using Relative-Distance Measures","authors":"K. Srinivasa, M. Jagadish, S. Prashanth, K. Venugopal, L. Patnaik","doi":"10.1109/ICISIP.2006.4286077","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286077","url":null,"abstract":"Protein sequence motifs are short conserved subsequences common to related protein sequences. Information about motifs is extremely important to the study of biologically significant conserved regions in protein families. These conserved regions can determine the functions and conformation of proteins. Conventionally, recurring patterns of proteins are explored using short protein segments and classification based on similarity measures between the segments. Two protein sequences are classified into the same class if they have high homology in terms of feature patterns extracted through sequence alignment algorithms. Such methodology focuses on finding position specific motifs only. In this paper, we propose a new algorithm to explore protein sequences by studying subsequences with relative-positioning of amino acids followed by K-Means clustering of fixed-sized segments. The dataset used for our work is most updated among studies for sequence motifs. The various biochemical tests that are found in literature are used to test the significance of motifs and these tests show that motifs generated are of both structural and functional interest. The results suggest that this method may also be applied to closely-related area of finding DNA motifs.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"87 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":"133649855","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":"Weighted Aggregation Scheme with Lifetime-Accuracy Tradeoff in Wireless Sensor Network","authors":"B. Jagyasi, B. Dey, S. Merchant, U. Desai","doi":"10.1109/ICISIP.2006.4286055","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286055","url":null,"abstract":"We consider design of wireless sensor network for event detection application. An MMSE based q-bit weighted aggregation scheme (q-WAS) is proposed in which each node transmits q bits to its parent in every session. The observation of each sensor is assumed to be one bit. The simulation results show that 1-WAS achieves better accuracy than a previously proposed one bit aggregation scheme while offering almost same lifetime. With increasing q, the accuracy of q-WAS approaches that of the infinite precision aggregation scheme. Moreover, the lifetime for q-WAS is significantly higher than infinite precision aggregation scheme. For a 100 node sensor network, the simulation results show that 3-WAS achieves a near optimum accuracy. The lifetime of the q-WAS is approximately 1/q-th of the lifetime of the one bit aggregation schemes. Hence this class of aggregation schemes offers a trade-off between accuracy and lifetime.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"115 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":"114494311","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":"Can Biological Motion be a Biometric?","authors":"P. Pati, A. Ramakrishnan","doi":"10.1109/ICISIP.2006.4286049","DOIUrl":"https://doi.org/10.1109/ICISIP.2006.4286049","url":null,"abstract":"Biological motion has successfully been used for analysis of a person's mood and other psychological traits. Efforts are made to use human gait as a non-invasive mode of biometric. In this reported work, we try to study the effectiveness of biological gait motion of people as a cue to biometric based person recognition. The data is 3D in nature and, hence, has more information with itself than the cues obtained from video-based gait patterns. The high accuracies of person recognition, using a simple linear model of data representation and simple neighborhood based classifiers, suggest that it is the nature of the data which is more important than the recognition scheme employed.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"9 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":"125212074","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}