Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045731
A. N. Kulkarni, S. Gandhe, P. Dhulekar, G. Phade
The demand for images in video sequences and computer animation has increased drastically over the years. This gives attention on an important issue of compression, resulting into reduction in cost of data storage and transmission. For still image compression JPEG is used world -wide. But alternative methods are also being explored; Fractal image compression is one of them. It is based on the self-similarity property to find out the best match within the image itself. This property is used to generate a fractal code. In this paper, the new approach for fractal image compression using genetic algorithm with ranking select mechanism is proposed. This proposed algorithm is applied on fractal as well as non-fractal images and the experimental result shows that the encoding time for both types of images is greatly reduced while maintaining their quality intact.
{"title":"Fractal image compression using genetic algorithm with ranking select mechanism","authors":"A. N. Kulkarni, S. Gandhe, P. Dhulekar, G. Phade","doi":"10.1109/ICCICT.2015.7045731","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045731","url":null,"abstract":"The demand for images in video sequences and computer animation has increased drastically over the years. This gives attention on an important issue of compression, resulting into reduction in cost of data storage and transmission. For still image compression JPEG is used world -wide. But alternative methods are also being explored; Fractal image compression is one of them. It is based on the self-similarity property to find out the best match within the image itself. This property is used to generate a fractal code. In this paper, the new approach for fractal image compression using genetic algorithm with ranking select mechanism is proposed. This proposed algorithm is applied on fractal as well as non-fractal images and the experimental result shows that the encoding time for both types of images is greatly reduced while maintaining their quality intact.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116899784","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}
Images with texture patterns have embedded feature of offering visual patterns, that have the property of homogeneity. They provide cardinal information pertaining to the structural arrangement of the surfaces. Huge databases containing such images require highly competent compression schemes. This paper proposes a compression scheme for gray-scale texture images based on a unique Discrete Wavelet Transform (DWT) Sub-band Elimination guided by energy thresholding. The algorithm operates on sub-bands generated by the wavelet transform and determines the dominating coefficients which contribute to the maximum energy. It then eliminates redundant coefficients and facilitates efficient compression ratio. The performance of the algorithm is evaluated by calculating various quality metrics viz. PSNR, MSE etc and plotting apposite graphs by experimenting on standard texture gray-scale image database.
{"title":"Energy thresholding based sub-band elimination DWT scheme for image compression","authors":"Afshan Mulla, Jaypal Baviskar, Pavankumar Borra, Sunita Yadav, Amol Baviskar","doi":"10.1109/ICCICT.2015.7045711","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045711","url":null,"abstract":"Images with texture patterns have embedded feature of offering visual patterns, that have the property of homogeneity. They provide cardinal information pertaining to the structural arrangement of the surfaces. Huge databases containing such images require highly competent compression schemes. This paper proposes a compression scheme for gray-scale texture images based on a unique Discrete Wavelet Transform (DWT) Sub-band Elimination guided by energy thresholding. The algorithm operates on sub-bands generated by the wavelet transform and determines the dominating coefficients which contribute to the maximum energy. It then eliminates redundant coefficients and facilitates efficient compression ratio. The performance of the algorithm is evaluated by calculating various quality metrics viz. PSNR, MSE etc and plotting apposite graphs by experimenting on standard texture gray-scale image database.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125025475","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045671
Shital Vaibhavraj Gharge, Srinu Dharavath
Wireless Sensor Network (WSN) has gained more importance in current era and given contribution on broad range of commercial applications. These networks consists of small, battery powered sensors communicating with each other to monitor the environment forming a network with ease of deployment where wired infrastructure is too expensive and difficult to deploy. In applications like home automation, health care monitoring multivendor and heterogeneous sensor nodes are deployed. For such applications virtualization in sensor network (VSN) may provide flexibility, ensure security and increase manageability. WSN implies various challenges in design and operations as major fact that sensor nodes run out of energy quickly has been an issue. So for energy consumption, better and improved clustering routing protocols are needed. This Paper surveys novel approach of using virtual sensor architecture and also presents improved clustering algorithm as efficient power saving scheme. Simulation results indicate superior performance of improved clustering algorithm in energy consumption and VSN approach reduces overall cost and complexity.
{"title":"Virtualization of Wireless Sensor Network with efficient power saving scheme","authors":"Shital Vaibhavraj Gharge, Srinu Dharavath","doi":"10.1109/ICCICT.2015.7045671","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045671","url":null,"abstract":"Wireless Sensor Network (WSN) has gained more importance in current era and given contribution on broad range of commercial applications. These networks consists of small, battery powered sensors communicating with each other to monitor the environment forming a network with ease of deployment where wired infrastructure is too expensive and difficult to deploy. In applications like home automation, health care monitoring multivendor and heterogeneous sensor nodes are deployed. For such applications virtualization in sensor network (VSN) may provide flexibility, ensure security and increase manageability. WSN implies various challenges in design and operations as major fact that sensor nodes run out of energy quickly has been an issue. So for energy consumption, better and improved clustering routing protocols are needed. This Paper surveys novel approach of using virtual sensor architecture and also presents improved clustering algorithm as efficient power saving scheme. Simulation results indicate superior performance of improved clustering algorithm in energy consumption and VSN approach reduces overall cost and complexity.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124537331","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045690
Nasheet Fatima
This paper proposes a system for transmission of image through OFDM system. To improve performance of system in terms of peak to average power ratio (PAPR) and Peak to signal noise ratio, Trigonometric Transforms such as DCT and DST are used.
{"title":"Image transmission over OFDM system using trigonometric transforms","authors":"Nasheet Fatima","doi":"10.1109/ICCICT.2015.7045690","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045690","url":null,"abstract":"This paper proposes a system for transmission of image through OFDM system. To improve performance of system in terms of peak to average power ratio (PAPR) and Peak to signal noise ratio, Trigonometric Transforms such as DCT and DST are used.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115585078","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045680
P. V. V. Reddy, L. Rajamani
Hypervisors enable multiple operating systems to run above it with the help of virtualization technique by sharing underlying physical resources. KVM hypervisor uses hybrid virtualization technique i.e., it uses full virtualization technique along with hardware assisted virtualization. It is motivating to analyse different Operating Systems (OSs) performance in the Private Cloud with KVM hypervisor. We have chosen three guest operating systems, namely Windows 2008 R2, Red Hat Enterprise Linux 5 (RHEL 5) and Ubuntu 10.04 Lucid Lynx (all are 64-bit) for the experimentation in the private cloud which is created using CloudStack. The three Operating Systems (OSs) are prudently chosen to represent three categories (Hardware virtualized guest or Hardware Virtual Machine (HVM), para-virtualized commercial guest and para-virtualized free guest). The performances of three Operating Systems have been planned to evaluate by creating low, medium and high workloads. The Operating Systems are compared by performance tests of CPU utilization, memory management, disk activity, and network communication. Important System information is gathered using SIGAR framework on the respective guest Operating System on KVM hypervisor.
虚拟机管理程序通过共享底层物理资源，借助虚拟化技术，使多个操作系统能够在其之上运行。KVM管理程序使用混合虚拟化技术，即使用完全虚拟化技术和硬件辅助虚拟化。使用KVM管理程序分析私有云中不同操作系统(os)的性能是一种激励。我们选择了三个客户操作系统，即Windows 2008 R2、Red Hat Enterprise Linux 5 (RHEL 5)和Ubuntu 10.04 Lucid Lynx(都是64位)，在使用CloudStack创建的私有云中进行实验。这三种操作系统经过精心选择，分别代表三种类型(硬件虚拟化客户端或硬件虚拟机(HVM)、半虚拟化的商业客户端和半虚拟化的自由客户端)。计划通过创建低、中、高工作负载来评估三种操作系统的性能。操作系统通过CPU利用率、内存管理、磁盘活动和网络通信的性能测试进行比较。重要的系统信息是在KVM管理程序上的相应客户机操作系统上使用SIGAR框架收集的。
{"title":"Performance comparison of different operating systems in the private cloud with KVM hypervisor using SIGAR framework","authors":"P. V. V. Reddy, L. Rajamani","doi":"10.1109/ICCICT.2015.7045680","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045680","url":null,"abstract":"Hypervisors enable multiple operating systems to run above it with the help of virtualization technique by sharing underlying physical resources. KVM hypervisor uses hybrid virtualization technique i.e., it uses full virtualization technique along with hardware assisted virtualization. It is motivating to analyse different Operating Systems (OSs) performance in the Private Cloud with KVM hypervisor. We have chosen three guest operating systems, namely Windows 2008 R2, Red Hat Enterprise Linux 5 (RHEL 5) and Ubuntu 10.04 Lucid Lynx (all are 64-bit) for the experimentation in the private cloud which is created using CloudStack. The three Operating Systems (OSs) are prudently chosen to represent three categories (Hardware virtualized guest or Hardware Virtual Machine (HVM), para-virtualized commercial guest and para-virtualized free guest). The performances of three Operating Systems have been planned to evaluate by creating low, medium and high workloads. The Operating Systems are compared by performance tests of CPU utilization, memory management, disk activity, and network communication. Important System information is gathered using SIGAR framework on the respective guest Operating System on KVM hypervisor.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123452362","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045729
Sudeep D. Thepade, Rupali K. Bhondave
Biometric identification verifies user identity by comparing an encoded value with a stored value of the concerned biometric characteristic. Multimodal person authentication system is more effective and more challenging. The fusion of multiple biometric traits helps to minimize the system error rate. The benefit of energy compaction of transforms in higher coefficients is taken here to reduce the feature vector size of image by taking fractional coefficients of transformed image. Smaller feature vector size results as less time for comparison of feature vectors resulting in faster identification. Iris and Palmprint are together taken here for bimodal biometric identification with fractional energy of Kekre, Walsh and Haar transformed Palm and Iris images. The test beds of 60 pairs of Iris and Palmprint samples of 10 persons (6 per person of iris as well asPalmprint) are used as test bed for experimentation. Experimental result that the show fractional coefficients perform better as indicatedby higher GAR values over consideration of 100% coefficients. In Walsh and haar transforms the bimodal identification of iris and Palmprint could not perform better than individual consideration of alone Palmprint but perform better than Iris. In Kekre transform bimodal with Palmprint and Iris has shown improvement in performance.
{"title":"Bimodal biometric identification with Palmprint and Iris traits using fractional coefficients of Walsh, Haar and Kekre transforms","authors":"Sudeep D. Thepade, Rupali K. Bhondave","doi":"10.1109/ICCICT.2015.7045729","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045729","url":null,"abstract":"Biometric identification verifies user identity by comparing an encoded value with a stored value of the concerned biometric characteristic. Multimodal person authentication system is more effective and more challenging. The fusion of multiple biometric traits helps to minimize the system error rate. The benefit of energy compaction of transforms in higher coefficients is taken here to reduce the feature vector size of image by taking fractional coefficients of transformed image. Smaller feature vector size results as less time for comparison of feature vectors resulting in faster identification. Iris and Palmprint are together taken here for bimodal biometric identification with fractional energy of Kekre, Walsh and Haar transformed Palm and Iris images. The test beds of 60 pairs of Iris and Palmprint samples of 10 persons (6 per person of iris as well asPalmprint) are used as test bed for experimentation. Experimental result that the show fractional coefficients perform better as indicatedby higher GAR values over consideration of 100% coefficients. In Walsh and haar transforms the bimodal identification of iris and Palmprint could not perform better than individual consideration of alone Palmprint but perform better than Iris. In Kekre transform bimodal with Palmprint and Iris has shown improvement in performance.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124830659","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045730
Sudeep D. Thepade, Lokesh S. Katore
Image compression is inevitable now a days as multimedia based data is increasing at faster rate. Vector Quantization plays vital role in Codebook generation. Codebook is the soul of Vector Quantization. There are several methods to generate Codebook but the recent one is Thepade's Cosine Error Vector Rotation (TCEVR), which is proven better than others (KEVR, KEVRW, LBG). Paper proposes novel Column based error Vector Rotation for TCEVR. The proposed column based improvisation in TCEVR is tested with a test bed of 18 images for image compression. Experimentation result show that the proposed TCEVR Codebook generation in VQ for Image compression is showing improvisation over earlier proposed Row based TCEVR. As observed from lower average Euclidean distance between the original and regenerated images for various Codebook sizes.
{"title":"Image compression using improvised column based Thepade's Cosine Error Vector Rotation (TCEVR) Codebook generation in Vector Quantization","authors":"Sudeep D. Thepade, Lokesh S. Katore","doi":"10.1109/ICCICT.2015.7045730","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045730","url":null,"abstract":"Image compression is inevitable now a days as multimedia based data is increasing at faster rate. Vector Quantization plays vital role in Codebook generation. Codebook is the soul of Vector Quantization. There are several methods to generate Codebook but the recent one is Thepade's Cosine Error Vector Rotation (TCEVR), which is proven better than others (KEVR, KEVRW, LBG). Paper proposes novel Column based error Vector Rotation for TCEVR. The proposed column based improvisation in TCEVR is tested with a test bed of 18 images for image compression. Experimentation result show that the proposed TCEVR Codebook generation in VQ for Image compression is showing improvisation over earlier proposed Row based TCEVR. As observed from lower average Euclidean distance between the original and regenerated images for various Codebook sizes.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127183950","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045727
Sudeep D. Thepade, Madhura Kalbhor
Important task in image database is to organize images into appropriate category using different features of images. Image classification is studied for many years. There are various techniques proposed to increase the accuracy of classification. In this paper a novel data mining based approach is proposed for content based image classification. Feature extraction and classification algorithms are two main steps in classification process. This paper proposes the use of orthogonal transform to generate the feature vector and to investigate effectiveness of different transforms (Cosine, Sine, and Walsh). Experimentation is carried on different sizes of feature vectors which are formed by taking fractional coefficients. Classification algorithm from different families such as Bayes (Naive Bayes and Bayes Net), Function (RBFNetwork and Simple Logistic), Lazy (IB1 and Kstar), Rule (Decision and Part) and Tree (BFTree, J48 Random Tree and Random Forest) are used for classification. Experimental results and its analysis have shown the Simple Logistic classifier with Walsh transform to be better for proposed data mining based image classification technique.
{"title":"Novel data mining based image classification with Bayes, Tree, Rule, Lazy and Function Classifiers using fractional row mean of Cosine, Sine and Walsh column transformed images","authors":"Sudeep D. Thepade, Madhura Kalbhor","doi":"10.1109/ICCICT.2015.7045727","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045727","url":null,"abstract":"Important task in image database is to organize images into appropriate category using different features of images. Image classification is studied for many years. There are various techniques proposed to increase the accuracy of classification. In this paper a novel data mining based approach is proposed for content based image classification. Feature extraction and classification algorithms are two main steps in classification process. This paper proposes the use of orthogonal transform to generate the feature vector and to investigate effectiveness of different transforms (Cosine, Sine, and Walsh). Experimentation is carried on different sizes of feature vectors which are formed by taking fractional coefficients. Classification algorithm from different families such as Bayes (Naive Bayes and Bayes Net), Function (RBFNetwork and Simple Logistic), Lazy (IB1 and Kstar), Rule (Decision and Part) and Tree (BFTree, J48 Random Tree and Random Forest) are used for classification. Experimental results and its analysis have shown the Simple Logistic classifier with Walsh transform to be better for proposed data mining based image classification technique.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129946567","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}
In the image processing domain, researchers all over the world aim at designing algorithms which posses the feature of facilitating multiple advantages amalgamated in one scheme viz. compression, fusion, enhancement, security etc. In various classified applications such as military, medical, forensics etc, the image databases are huge and contain a lot of information. Hence, compression of these high-quality images and securing these databases becomes imperative. This paper proposes a Discrete Wavelet Transform (DWT) guided image compression as well as image security technique. The RGB color images are converted into textured images by exploiting DWT properties and thereby facilitating image compression. Since this process is reversible, the colors in the image are retrieved back from the texture patterns. In addition, the security of the image is enhanced based on a novel probabilistic triangular shuffling scheme. The overall proposed algorithm assists in achieving 67-70% compression ratio and improved security. Evaluating the performance of the algorithm, various graphs pertaining to PSNR, MSE, probability of security breach are realized.
{"title":"Probabilistic triangular shuffling approach in DWT based image compression scheme","authors":"Afshan Mulla, Jaypal Baviskar, Swapnil Wagh, Neha Kudu, Amol Baviskar","doi":"10.1109/ICCICT.2015.7045658","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045658","url":null,"abstract":"In the image processing domain, researchers all over the world aim at designing algorithms which posses the feature of facilitating multiple advantages amalgamated in one scheme viz. compression, fusion, enhancement, security etc. In various classified applications such as military, medical, forensics etc, the image databases are huge and contain a lot of information. Hence, compression of these high-quality images and securing these databases becomes imperative. This paper proposes a Discrete Wavelet Transform (DWT) guided image compression as well as image security technique. The RGB color images are converted into textured images by exploiting DWT properties and thereby facilitating image compression. Since this process is reversible, the colors in the image are retrieved back from the texture patterns. In addition, the security of the image is enhanced based on a novel probabilistic triangular shuffling scheme. The overall proposed algorithm assists in achieving 67-70% compression ratio and improved security. Evaluating the performance of the algorithm, various graphs pertaining to PSNR, MSE, probability of security breach are realized.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132006503","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}
Pub Date : 2015-02-23DOI: 10.1109/ICCICT.2015.7045676
Swathi Melkundi, Chaitali Chandankhede
Outsourcing of data is increasing with the rapid growth of internet. There is every possibility that data reaches illegal hands. As a result, there is increase in illegal copying of data, piracy, illegal redistribution, forgery and theft. Watermarking technology is a solution for these challenges. It addresses the ownership problem. It deters illegal copying and protects copyright of data. Watermarking technology mainly involves the process of watermark insertion and watermark extraction. Watermark insertion means embedding an imperceptible watermark in the relational database. In watermark extraction we extract the embedded watermark without the help of original database. In this paper we propose a new watermarking technique, which will watermark both textual and numerical data. Our proposed method also does watermark verification where, the watermark extracted from the database is compared with the original watermark that is known only to the owner of the database. This is accomplished through Levenshtein distance algorithm.
{"title":"A robust technique for relational database watermarking and verification","authors":"Swathi Melkundi, Chaitali Chandankhede","doi":"10.1109/ICCICT.2015.7045676","DOIUrl":"https://doi.org/10.1109/ICCICT.2015.7045676","url":null,"abstract":"Outsourcing of data is increasing with the rapid growth of internet. There is every possibility that data reaches illegal hands. As a result, there is increase in illegal copying of data, piracy, illegal redistribution, forgery and theft. Watermarking technology is a solution for these challenges. It addresses the ownership problem. It deters illegal copying and protects copyright of data. Watermarking technology mainly involves the process of watermark insertion and watermark extraction. Watermark insertion means embedding an imperceptible watermark in the relational database. In watermark extraction we extract the embedded watermark without the help of original database. In this paper we propose a new watermarking technique, which will watermark both textual and numerical data. Our proposed method also does watermark verification where, the watermark extracted from the database is compared with the original watermark that is known only to the owner of the database. This is accomplished through Levenshtein distance algorithm.","PeriodicalId":324889,"journal":{"name":"2015 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132150086","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}
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