Debasri Saha, P. Dasgupta, S. Sur-Kolay, S. Sen-Sarma
{"title":"A Novel Scheme for Encoding and Watermark Embedding in VLSI Physical Design for IP Protection","authors":"Debasri Saha, P. Dasgupta, S. Sur-Kolay, S. Sen-Sarma","doi":"10.1109/ICCTA.2007.17","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.17","url":null,"abstract":"The emerging trend of design reuse in VLSI circuits poses the threat of theft and misappropriation of intellectual property (IP) of the design. Protection of design IP is a matter of prime concern today. We propose a scheme SECURE_IP, which tackles the problem from an entirely new viewpoint. It relies on the application of cryptographic principles and the watermarking techniques to provide both direct and indirect IP protection in VLSI physical design. It makes unauthorized disclosure of a valuable design infeasible during its transmission, and can easily detect any alteration of the design file during transmission. The proposed scheme ensures authentication of the original designer as well as non-repudiation between the designer (seller) and the buyer. Illegal reselling can be efficiently detected by the proposed scheme. The algorithm SECURE_IP is tested on random and MCNC benchmark instances, and the experimental results are quite encouraging","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121143688","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 Comparative Study on 2D Curvature Estimators","authors":"S. Hermann, R. Klette","doi":"10.1109/ICCTA.2007.2","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.2","url":null,"abstract":"Curvature is a frequently used property in two-dimensional (2D) shape analysis, directly or for derived features such as corners or convex and concave arcs. This paper presents curvature estimators which follow approaches in differential geometry. Digital-straight segment approximation (as known from digital geometry) is used in those estimators. Results of multigrid experiments are evaluated leading to a comparative performance analysis of several curvature estimators","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116931340","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 Low-Cost Pipelineed Multi-Lingual E-Dictionary Using a Pipelined CTAM","authors":"S. K. Ray, Sabyasachi Dutta, A. Saha","doi":"10.1109/ICCTA.2007.11","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.11","url":null,"abstract":"A pipelined multi-lingual electronic dictionary (PMLeD) has been designed and implemented. Architecturally, it is a pipeline of four memory stages of which the first one is itself a pipelined version of a content-to-address-memory (CTAM) while the other three are traditional address-to-content memories (ATCM), namely, RAMs. The PMLeD is potentially capable of providing millions of word-by-word translations per second between an arbitrarily large number of languages but requires a highly expensive fully parallel design of the pipelined CTAM (PCTAM) stages for achieving this high throughput rate. The present design, which has been implemented and tested in the laboratory, has studied a cost-performance trade-off by designing each stage in the PCTAM with a byte-serial approach and implementing it employing a low-cost 8-bit microcontroller. The design has achieved a hefty reduction in cost and complexity at a considerable sacrifice in the throughput rate and marks a novel, simple and low-cost practical design approach to a pipelined associative memory","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121618327","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":"Algorithm for Identifying the Syntactic and Semantic Categories of Prepositions: Case of Over","authors":"Yukiko Sasaki Alam","doi":"10.1109/ICCTA.2007.24","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.24","url":null,"abstract":"This paper proposes an algorithm for assigning the syntactic categories of over, many uses of which are not used as prepositions. The algorithm, enriched for the semantic capacity from earlier studies, identifies four syntactic categories of over and eleven meanings of the prepositional uses. The ability of the algorithm was tested manually by using five hundred instances of over from British National Corpus. The results are encouraging, with over 95 percent of the instances being correctly classified. This study, while pointing to an ideal direction, will reveal many important points to consider in natural language processing","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126209820","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}
S. Thakur, J. Sing, D. K. Basu, M. Nasipuri, M. Kundu
{"title":"Face Recognition by Combination of RBF Neural Networks Using Dempster-Shafer Theory","authors":"S. Thakur, J. Sing, D. K. Basu, M. Nasipuri, M. Kundu","doi":"10.1109/ICCTA.2007.59","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.59","url":null,"abstract":"This paper presents an approach to face recognition based on Dempster-Shafer (DS) theory of evidence, which combines the evidences of two radial basis function (RBF) neural networks. The degrees of belief of the two RBF neural networks for classification of an image have been estimated using two different feature vectors derived from images of the ORL face database. Then these degrees of belief have been combined using DS theory to improve the overall recognition rates. The average recognition rates of the proposed method have been found to be 83.78%, 88.08%, 97.10%, 98.06% and 97.75%, in 10 different experimental runs of 3, 4, 5, 6 and 7 training images out of 10 images per individual, respectively. The proposed method is found to be better than some of the existing methods","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114338377","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 Fuzzy Genetic Clustering Technique Using a New Symmetry Based Distance for Automatic Evolution of Clusters","authors":"S. Saha, S. Bandyopadhyay","doi":"10.1109/ICCTA.2007.5","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.5","url":null,"abstract":"In this paper a fuzzy point symmetry based genetic clustering technique (fuzzy-VGAPS) is proposed which can determine the number of clusters present in a data set as well as a good fuzzy partitioning of the data. A new fuzzy cluster validity index, FSym-index, which is based on the newly developed point symmetry based distance is also proposed here. FSym-index provides a measure of goodness of clustering on different fuzzy partitions of a data set. Maximum value of FSym-index corresponds to the proper clustering present in a data set. The flexibility of fuzzy-VGAPS is utilized in conjunction with the fuzzy FSym-index to determine the number of clusters present in a data set as well as a good fuzzy partition of the data. The results of the fuzzy VGAPS are compared with those obtained by fuzzy version of variable string length genetic clustering technique (fuzzy-VGA) optimizing XB-index. The effectiveness of the fuzzy-VGAPS is demonstrated on four artificial data sets and two real-life data sets","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121843726","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":"Cache-Oblivious Computation: Algorithms and Experimental Evaluation","authors":"V. Ramachandran","doi":"10.1109/ICCTA.2007.34","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.34","url":null,"abstract":"We describe our recent research results on cache-oblivious algorithms for certain types of dynamic programs and triply-nested loop computations, and for priority queues and their application in shortest path problems in graphs. We present some preliminary results from our ongoing experimental work on comparing our cache-oblivious algorithms to currently available code for these problems. Our results demonstrate that cache-oblivious methods can give rise to efficient algorithms both in theory and in practice","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122130079","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":"Analysis of Ultrasound Kidney Images Using Content Descriptive Multiple Features for Disorder Identification and ANN Based Classification","authors":"K. B. Raja, M. Madheswaran, K. Thyagarajah","doi":"10.1109/ICCTA.2007.31","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.31","url":null,"abstract":"The objective of this work is to provide a set of most significant content descriptive feature parameters to identify and classify the kidney disorders with ultrasound scan. The ultrasound images are initially pre-processed to preserve the pixels of interest prior to feature extraction. In total 28 features are extracted, the analysis of features value shows that 13 features are highly significant in discrimination. This resultant feature vector is used to train the multilayer back propagation network. The network is tested with the unknown samples. The outcome of multi-layer back propagation network is verified with medical experts and this confirms classification efficiency of 90.47%, 86.66%, and 85.71% for the classes considered respectively. The study shows that feature extraction after pre-processing followed by ANN based classification significantly enhance objective diagnosis and provides the possibility of developing computer-aided diagnosis system","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129865561","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":"Stabilisation of Active Contours Using Tangential Evolution: An Application to Tracking","authors":"V. Srikrishnan, S. Chaudhuri, Sumantra Dutta Roy","doi":"10.1109/ICCTA.2007.121","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.121","url":null,"abstract":"Active contours are very widely used in computer vision problems. Their usage has a typical problem, that of bunching together of curve points. This becomes apparent especially when we use active contours for tracking, leading to instability in curve evolution. In this paper, we propose an additional tangential term to stabilise the evolution while at the same time ensure that the curve shape is not changed. The proposed method is simple and the computational overhead is minimal, while the results are good","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128773878","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":"Indexing of Document Images Based on Triangular Spatial Relationships","authors":"P. Punitha, Naveen Onkarappa, D. S. Guru","doi":"10.1109/ICCTA.2007.73","DOIUrl":"https://doi.org/10.1109/ICCTA.2007.73","url":null,"abstract":"In this paper, a new scheme of indexing document images based on B-tree by preserving triangular spatial relationships (TSR) among the components of a document image is proposed. A new technique for labeling of components in document images is also proposed. A procedure for classifying retrieved images and a method of ranking the retrieved document images are also proposed. The retrieval results of the proposed TSR based indexing scheme is compared with nine-directional codes based (NDC) indexing scheme and also with the retrieval results of human experts. The experiments are conducted on the MediaTeam document image database that provides diverse collection of document images","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121165669","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}