Pub Date : 2012-04-30DOI: 10.5121/IJCSES.2012.3206
Shwetambari Shinde, Meeta Dewangan
Methods for super-resolution can be broadly classified into two families of methods: (i) The classical multi-image super-resolution (combining images obtained at subpixel misalignments), and (ii) ExampleBased super-resolution (learning correspondence between low and high resolution image patches from a database). In this paper we propose a unified framework for combining these two families of methods. We further show how this combined approach can be applied to obtain super resolution from as little as a single image (with no database or prior examples). Our approach is based on the observation that patches in a natural image tend to redundantly recur many times inside the image, both within the same scale, as well as across different scales. Recurrence of patches within the same image scale (at sub pixel misalignments) gives rise to the classical super-resolution, whereas recurrence of patches across different scales of the same image gives rise to example-based super-resolution. Our approach attempts to recover at each pixel its best possible resolution increase based on its patch redundancy within and across scales.
{"title":"Single Image Improvement using Superresolution.","authors":"Shwetambari Shinde, Meeta Dewangan","doi":"10.5121/IJCSES.2012.3206","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3206","url":null,"abstract":"Methods for super-resolution can be broadly classified into two families of methods: (i) The classical multi-image super-resolution (combining images obtained at subpixel misalignments), and (ii) ExampleBased super-resolution (learning correspondence between low and high resolution image patches from a database). In this paper we propose a unified framework for combining these two families of methods. We further show how this combined approach can be applied to obtain super resolution from as little as a single image (with no database or prior examples). Our approach is based on the observation that patches in a natural image tend to redundantly recur many times inside the image, both within the same scale, as well as across different scales. Recurrence of patches within the same image scale (at sub pixel misalignments) gives rise to the classical super-resolution, whereas recurrence of patches across different scales of the same image gives rise to example-based super-resolution. Our approach attempts to recover at each pixel its best possible resolution increase based on its patch redundancy within and across scales.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115025576","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 : 2012-04-30DOI: 10.5121/IJCSES.2012.3202
Taresh Singh, S. Qamar
The recognition is a new security principle closely related to authentication. Low-power ad hoc networks with no pre-deployment information require the less authoritative security in recognition. We have studied previously proposed low-power protocols according to the environment and security model presented. We have implemented the New Message Recognition Protocol (NMRP) and Zero Common Knowledge (ZCK) protocol in C and matlab. From our comparison between NMRP and ZCK, we observed that NMRP satisfied the properties of low power environment.
{"title":"Energy Efficient Recognition Protocol for Ad Hoc Networks","authors":"Taresh Singh, S. Qamar","doi":"10.5121/IJCSES.2012.3202","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3202","url":null,"abstract":"The recognition is a new security principle closely related to authentication. Low-power ad hoc networks with no pre-deployment information require the less authoritative security in recognition. We have studied previously proposed low-power protocols according to the environment and security model presented. We have implemented the New Message Recognition Protocol (NMRP) and Zero Common Knowledge (ZCK) protocol in C and matlab. From our comparison between NMRP and ZCK, we observed that NMRP satisfied the properties of low power environment.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129795680","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 : 2012-04-30DOI: 10.5121/IJCSES.2012.3203
R. Khan
A number of load balancing algorithms were developed in order to improve the execution of a distributed application in any kind of distributed architecture. Load balancing involves assigning tasks to each processor and minimizing the execution time of the program. In practice, it would be possible even to execute the applications on any machine of worldwide distributed systems. However, the ‘distributed system’ becomes popular and attractive with the introduction of the web. This results in a significant performance improvement for the users. This paper describes the necessary, newly developed, principal concepts for several load balancing techniques in a distributed computing environment. This paper also includes various types of load balancing strategies, their merits, demerits and comparison depending on certain parameters.
{"title":"THE STUDY ON LOAD BALANCING STRATEGIES IN DISTRIBUTED COMPUTING SYSTEM","authors":"R. Khan","doi":"10.5121/IJCSES.2012.3203","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3203","url":null,"abstract":"A number of load balancing algorithms were developed in order to improve the execution of a distributed application in any kind of distributed architecture. Load balancing involves assigning tasks to each processor and minimizing the execution time of the program. In practice, it would be possible even to execute the applications on any machine of worldwide distributed systems. However, the ‘distributed system’ becomes popular and attractive with the introduction of the web. This results in a significant performance improvement for the users. This paper describes the necessary, newly developed, principal concepts for several load balancing techniques in a distributed computing environment. This paper also includes various types of load balancing strategies, their merits, demerits and comparison depending on certain parameters.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132346266","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3110
Sesha Pallavi Indrakanti, S. AvadhaniP.
Security is playing a vital role in this era of information technology, it has become a prerequisite in the digital world for maintaining the secrecy of the information. Many techniques have been proposed for handling textual data, maintenance of confidentiality of pictographic data is also becoming a priority. The trend of pictographic data hiding is pixel based, here a version of Visual Cryptography is presented which is segment-based instead of pixel based. The key or the secret which is in the form of digits that is to be distributed is converted into segment display and then encrypted .The result of encryption is two random shares. The decryption process involves the stacking of these two shares. It is easier to view the secret with the human eye by stacking the shares.
{"title":"SEGMENT BASED VISUAL CRYPTOGRAPHY FOR KEY DISTRIBUTION","authors":"Sesha Pallavi Indrakanti, S. AvadhaniP.","doi":"10.5121/IJCSES.2012.3110","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3110","url":null,"abstract":"Security is playing a vital role in this era of information technology, it has become a prerequisite in the digital world for maintaining the secrecy of the information. Many techniques have been proposed for handling textual data, maintenance of confidentiality of pictographic data is also becoming a priority. The trend of pictographic data hiding is pixel based, here a version of Visual Cryptography is presented which is segment-based instead of pixel based. The key or the secret which is in the form of digits that is to be distributed is converted into segment display and then encrypted .The result of encryption is two random shares. The decryption process involves the stacking of these two shares. It is easier to view the secret with the human eye by stacking the shares.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117281279","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3112
S. Kosbatwar
The use of artificial neural network in applications can dramatically simplify the code and improve quality of recognition while achieving good performance. Another benefit of using neural network in application is extensibility of the system – ability to recognize more character sets than initially defined. Most of traditional systems are not extensible enough. In this paper recognition of characters is possible by using neural network back propagation algorithm. What is neural network Neural network are simplified models of the biological nervous system and therefore have drawn their motivation from the kind of computing performed by a human brain. An NN in general is a highly interconnected of a large number of processing elements called neurons in an architecture inspired by the brain. An NN can be massively parallel and therefore is said to exhibit parallel distributed processing. Neural Network exhibits characteristics such as mapping capabilities or pattern association, generalization, robustness, fault tolerance, and parallel and high speed information processing. Neural network learn by example. They can therefore be trained with known examples of a problem to acquire knowledge about it. Once appropriate trained the network can be put to effective use in solving ‘unknown’ or ‘untrained’ instances of the problem. Neural network adopt various learning mechanism of which supervised learning and unsupervised learning methods have turned out to be very popular. In supervised learning, a teacher is assumed to be present during the learning process, i.e. the network aims to minimize he error between target (desired) output presented by the teacher and the computed output to achieve better performance. However, in unsupervised learning, there is no teacher present to hand over the desired output and the network therefore tries to learn by itself, organizing the input instances of the problem.NN Architecture has been broadly classified as single layer feed forward networks, multilayer feed forward networks and recurrent networks, over the year several other NN.Architecture have evolved .some of the well known NN system include backpropogation network, perceptron, ADALINE ,Boltzmann machine ,adaptive resonance theory, Self-organized feature map, and Hopfield network. Neural Network has been successfully applied to problem in the field of pattern recognition, image processing, data compression, forecasting and optimization to quote a few. International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.1, February 2012 128 Backpropagation algorithm The architecture of the neural network is the one of a basically backpropagation network with only one hidden layer (although it is the same techniques with more layers). The input layer is constituted of 35 neuron (one per input pixel in the matrix, of course)., they are 8 hidden neurons, and 26 output neurons(one per letter) in this problem domain of character recognition. The weight m
{"title":"Pattern Association For Character Recognition By Back-Propagation Algorithm Using Neural Network Approach","authors":"S. Kosbatwar","doi":"10.5121/IJCSES.2012.3112","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3112","url":null,"abstract":"The use of artificial neural network in applications can dramatically simplify the code and improve quality of recognition while achieving good performance. Another benefit of using neural network in application is extensibility of the system – ability to recognize more character sets than initially defined. Most of traditional systems are not extensible enough. In this paper recognition of characters is possible by using neural network back propagation algorithm. What is neural network Neural network are simplified models of the biological nervous system and therefore have drawn their motivation from the kind of computing performed by a human brain. An NN in general is a highly interconnected of a large number of processing elements called neurons in an architecture inspired by the brain. An NN can be massively parallel and therefore is said to exhibit parallel distributed processing. Neural Network exhibits characteristics such as mapping capabilities or pattern association, generalization, robustness, fault tolerance, and parallel and high speed information processing. Neural network learn by example. They can therefore be trained with known examples of a problem to acquire knowledge about it. Once appropriate trained the network can be put to effective use in solving ‘unknown’ or ‘untrained’ instances of the problem. Neural network adopt various learning mechanism of which supervised learning and unsupervised learning methods have turned out to be very popular. In supervised learning, a teacher is assumed to be present during the learning process, i.e. the network aims to minimize he error between target (desired) output presented by the teacher and the computed output to achieve better performance. However, in unsupervised learning, there is no teacher present to hand over the desired output and the network therefore tries to learn by itself, organizing the input instances of the problem.NN Architecture has been broadly classified as single layer feed forward networks, multilayer feed forward networks and recurrent networks, over the year several other NN.Architecture have evolved .some of the well known NN system include backpropogation network, perceptron, ADALINE ,Boltzmann machine ,adaptive resonance theory, Self-organized feature map, and Hopfield network. Neural Network has been successfully applied to problem in the field of pattern recognition, image processing, data compression, forecasting and optimization to quote a few. International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.1, February 2012 128 Backpropagation algorithm The architecture of the neural network is the one of a basically backpropagation network with only one hidden layer (although it is the same techniques with more layers). The input layer is constituted of 35 neuron (one per input pixel in the matrix, of course)., they are 8 hidden neurons, and 26 output neurons(one per letter) in this problem domain of character recognition. The weight m","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116609292","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3111
B. Maheshwari
We consider several distributed collaborative key agreement and authentication protocols for dynamic peer groups. There are several important characteristics which make this problem different from traditional secure group communication. They are: 1) Distributed nature in which there is no centralized key server; 2) Collaborative nature in which the group key is contributory (i.e., each group member will collaboratively contribute its part to the global group key); and 3) Dynamic nature in which existing members may leave the group while new members may join. Instead of performing individual rekeying operations, i.e. recomputing the group key after every join or leave request, we discuss an interval-based approach of rekeying. We consider three intervalbased distributed rekeying algorithms, or interval-based algorithms for short, for updating the group key: 1) the Rebuild algorithm; 2) the Batch algorithm; and 3) the Queue-batch algorithm. Performance of these three interval-based algorithms under different settings, such as different join and leave probabilities, is analyzed. We show that the interval-based algorithms significantly outperform the individual rekeying approach and that the Queue-batch algorithm performs the best among the three interval-based algorithms. More importantly, the Queue-batch algorithm can substantially reduce the computation and communication workload in a highly dynamic environment. We further enhance the interval-based algorithms in two aspects: authentication and implementation. Authentication focuses on the security improvement, while implementation realizes the interval-based algorithms in real network settings. Our work provides a fundamental understanding about establishing a group key via a distributed and collaborative approach for a dynamic peer group.
{"title":"SECURE KEY AGREEMENT AND AUTHENTICATION PROTOCOLS","authors":"B. Maheshwari","doi":"10.5121/IJCSES.2012.3111","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3111","url":null,"abstract":"We consider several distributed collaborative key agreement and authentication protocols for dynamic peer groups. There are several important characteristics which make this problem different from traditional secure group communication. They are: 1) Distributed nature in which there is no centralized key server; 2) Collaborative nature in which the group key is contributory (i.e., each group member will collaboratively contribute its part to the global group key); and 3) Dynamic nature in which existing members may leave the group while new members may join. Instead of performing individual rekeying operations, i.e. recomputing the group key after every join or leave request, we discuss an interval-based approach of rekeying. We consider three intervalbased distributed rekeying algorithms, or interval-based algorithms for short, for updating the group key: 1) the Rebuild algorithm; 2) the Batch algorithm; and 3) the Queue-batch algorithm. Performance of these three interval-based algorithms under different settings, such as different join and leave probabilities, is analyzed. We show that the interval-based algorithms significantly outperform the individual rekeying approach and that the Queue-batch algorithm performs the best among the three interval-based algorithms. More importantly, the Queue-batch algorithm can substantially reduce the computation and communication workload in a highly dynamic environment. We further enhance the interval-based algorithms in two aspects: authentication and implementation. Authentication focuses on the security improvement, while implementation realizes the interval-based algorithms in real network settings. Our work provides a fundamental understanding about establishing a group key via a distributed and collaborative approach for a dynamic peer group.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129792641","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3102
T. Nalini, Dr. A. Kumaravel, Dr. K. Rangarajan
Materialized view selection is one of the most crucial techniques to design data warehouse in an optimal manner. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views to materialize which minimizes the sum of total query response time and maintenance of the selected views is defined as view selection problem. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key objective of data warehousing. In this paper we compare the various research works on several parameters for controlling the selection process and also we compare time, query frequency and spatial cost.
{"title":"A comparative study analysis of materialized view for selection cost","authors":"T. Nalini, Dr. A. Kumaravel, Dr. K. Rangarajan","doi":"10.5121/IJCSES.2012.3102","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3102","url":null,"abstract":"Materialized view selection is one of the most crucial techniques to design data warehouse in an optimal manner. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views to materialize which minimizes the sum of total query response time and maintenance of the selected views is defined as view selection problem. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key objective of data warehousing. In this paper we compare the various research works on several parameters for controlling the selection process and also we compare time, query frequency and spatial cost.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130595705","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3104
K. .. Rao, A. Govardhan, K. V. C. Rao
Spatiotemporal data usually contain the states of an object, an event or a position in space over a period of time. Vast amount of spatiotemporal data can be found in several application fields such as traffic management, environment monitoring, and weather forecast. These datasets might be collected at different locations at various points of time in different formats. It poses many challenges in representing, processing, analysis and mining of such datasets due to complex structure of spatiotemporal objects and the relationships among them in both spatial and temporal dimensions. In this paper, the issues and challenges related to spatiotemporal data representation, analysis, mining and visualization of knowledge are presented. Various kinds of data mining tasks such as association rules, classification clustering for discovering knowledge from spatiotemporal datasets are examined and reviewed. System functional requirements for such kind of knowledge discovery and database structure are discussed. Finally applications of spatiotemporal data mining are presented.
{"title":"SPATIOTEMPORAL DATA MINING : ISSUES , TASKS AND APPLICATIONS","authors":"K. .. Rao, A. Govardhan, K. V. C. Rao","doi":"10.5121/IJCSES.2012.3104","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3104","url":null,"abstract":"Spatiotemporal data usually contain the states of an object, an event or a position in space over a period of time. Vast amount of spatiotemporal data can be found in several application fields such as traffic management, environment monitoring, and weather forecast. These datasets might be collected at different locations at various points of time in different formats. It poses many challenges in representing, processing, analysis and mining of such datasets due to complex structure of spatiotemporal objects and the relationships among them in both spatial and temporal dimensions. In this paper, the issues and challenges related to spatiotemporal data representation, analysis, mining and visualization of knowledge are presented. Various kinds of data mining tasks such as association rules, classification clustering for discovering knowledge from spatiotemporal datasets are examined and reviewed. System functional requirements for such kind of knowledge discovery and database structure are discussed. Finally applications of spatiotemporal data mining are presented.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"133 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113996599","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 : 2012-02-29DOI: 10.5121/IJCSES.2012.3106
Dolley Shukla, Manisha Sharma, S. Shankaracharya
DIGITAL WATERMARKING IS THE PROCESS OF EMBEDDING INFORMATION INTO A DIGITAL SIGNAL, I.E. AUDIO , PICTURES , VIDEO , ETC . EMBEDDED MARKS IN THE MESSAGE ARE GENERALLY IMPERCEPTIBLE BUT CAN BE DETECTED OR EXTRACTED. THE EMBEDDING TAKES PLACE BY MANIPULATING THE CONTENT OF THE DIGITAL DATA , WHICH MEANS THE INFORMATION IS NOT EMBEDDED IN THE FRAME AROUND THE DATA . IF THE SIGNAL IS COPIED , THEN THE EMBEDDED INFORMATION IS ALSO IN THE COPY . BY IMPERCEPTIBLY HIDING INFORMATION INTO THE VIDEO CONTENT IT WILL BE POSSIBLE TO PREVENT COPYING OR PLAYBACK OF SUCH CONTENT . SO , WATERMARKING IS AN EMERGING TECHNOLOGY THAT IS CLAIMED TO HAVE AN IMPORTANT APPLICATION IN COPY PROTECTION . A VARIETY OF WATERMARKING TECHNIQUES HAVE BEEN PROPOSED BY RESEARCHERS FOR THE COPY -PROTECTION . THIS PAPER PRESENTS AN EXTENSIVE REVIEW OF THE PREVAILING LITERATURE IN WATERMARKING FOR COPY PROTECTION .
{"title":"WATERMARKING SCHEMES FOR COPY PROTECTION : A SURVEY","authors":"Dolley Shukla, Manisha Sharma, S. Shankaracharya","doi":"10.5121/IJCSES.2012.3106","DOIUrl":"https://doi.org/10.5121/IJCSES.2012.3106","url":null,"abstract":"DIGITAL WATERMARKING IS THE PROCESS OF EMBEDDING INFORMATION INTO A DIGITAL SIGNAL, I.E. AUDIO , PICTURES , VIDEO , ETC . EMBEDDED MARKS IN THE MESSAGE ARE GENERALLY IMPERCEPTIBLE BUT CAN BE DETECTED OR EXTRACTED. THE EMBEDDING TAKES PLACE BY MANIPULATING THE CONTENT OF THE DIGITAL DATA , WHICH MEANS THE INFORMATION IS NOT EMBEDDED IN THE FRAME AROUND THE DATA . IF THE SIGNAL IS COPIED , THEN THE EMBEDDED INFORMATION IS ALSO IN THE COPY . BY IMPERCEPTIBLY HIDING INFORMATION INTO THE VIDEO CONTENT IT WILL BE POSSIBLE TO PREVENT COPYING OR PLAYBACK OF SUCH CONTENT . SO , WATERMARKING IS AN EMERGING TECHNOLOGY THAT IS CLAIMED TO HAVE AN IMPORTANT APPLICATION IN COPY PROTECTION . A VARIETY OF WATERMARKING TECHNIQUES HAVE BEEN PROPOSED BY RESEARCHERS FOR THE COPY -PROTECTION . THIS PAPER PRESENTS AN EXTENSIVE REVIEW OF THE PREVAILING LITERATURE IN WATERMARKING FOR COPY PROTECTION .","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124737664","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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