This paper proposes a simple data hiding technique for binary images. The binary cover image is partitioned into equal-sized, non-overlapping blocks and the watermark will be embedded into blocks by flipping pixels. T...
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ISBN:
(纸本)9780769529943;0769529941
This paper proposes a simple data hiding technique for binary images. The binary cover image is partitioned into equal-sized, non-overlapping blocks and the watermark will be embedded into blocks by flipping pixels. The weight mechanism is also proposed to find the most suitable flip pixel in the block. In order to improve the visual quality of the stego image, the boundary check is used to prevent the boundary distortion. Experimental results show that our method achieves a good visual quality for the watermarked image and has high capacity for embedding.
This paper focuses on the study of combination of some of the existing clustering methods and utilizing them meaningfully for feature dimensionality reduction. The efficacy of different cluster validity indices is inv...
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ISBN:
(纸本)9781467378086
This paper focuses on the study of combination of some of the existing clustering methods and utilizing them meaningfully for feature dimensionality reduction. The efficacy of different cluster validity indices is investigated in selecting good features. A fuzzy ART network is used for experimentation. Colon dataset, wine dataset and iris dataset are used in this study to see the effectiveness of combination of different techniques of cluster validity and clustering in feature reduction. The proposed method of clustering and then reducing the features seems to be very powerful to be used on huge bioinformatics datasets to reduce the number of redundant features.
A multi-processor system is an integrated circuit containing multiple processor cores that implements most of the functionality of a complex electronic system and some other components like FPGA/ASIC on a single chip....
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A multi-processor system is an integrated circuit containing multiple processor cores that implements most of the functionality of a complex electronic system and some other components like FPGA/ASIC on a single chip. In this paper, we present a novel approach to synthesize multi-core system architectures from Task Precedence Graphs (TPG) models. The front end engine applies efficient algorithm for scheduling and communication contention resolving to obtain the optimal multi-core system architecture in terms of number of processor cores, number of busses, task-to-processor/channel-to-bus mapping, optimal schedule, and hardware-software (HW-SW) partition. The scheduling and mapping algorithms produce the optimality of mapping tasks onto cores. The partitioning technique reduces the overall execution time and number of buses among the cores. The back end engine generates a SystemC simulation model using a well-known commercial tool model generation library. The viability and potential of the proposed algorithms are demonstrated by a case study and extensive experimental results to conclude that the proposed approach is an efficient scheme to obtain the optimality of scheduling, mapping and partitioning with hard and large task graph problems.
Association rules are widely used to extract patterns from a given database. The association rules are capable of finding correlations among items, making it possible for the user to learn which items are present in t...
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Association rules are widely used to extract patterns from a given database. The association rules are capable of finding correlations among items, making it possible for the user to learn which items are present in the transactions and which of them have a significant correlation. One of the major problems with association rules is that the number of extracted rules usually exceeds the number of transactions present in the database, also surpassing the user's capability to explore the obtained knowledge. To overcome this problem, the post-processing phase was proposed with the objective of directing the user to the rules that potentially have the most interesting knowledge. One of the used approaches is to divide the association rules into groups (or clusters), so that rules behave similarly are on the same group, facilitating the rule set understanding. In the literature, there are some works that uses clustering algorithms to split the rules while some other works use community detection algorithms. As both approaches obtain groups of association rules, but using different premises, different results can be obtained. No study has been done on the differences among clustering and community detection algorithms, which makes the selection of the algorithm hard, once their behavior is not well known in the association rule post-processing phase. This paper presents an analysis on both approaches, aiming to find the differences and the similarities among them, making it easier to select an approach by knowing its behavior.
The RSU deployment algorithms to cover interest regions have emerged as promising areas of research in vehicular ad hoc networks. However, there is few research on the discovery of the interest regions. Besides, the d...
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ISBN:
(纸本)9781479935130
The RSU deployment algorithms to cover interest regions have emerged as promising areas of research in vehicular ad hoc networks. However, there is few research on the discovery of the interest regions. Besides, the deployment algorithms are usually proposed for either continuous coverage or sparse coverage. The wisdom of the model selection are rarely addressed. In this paper, we proposed a new algorithm to discover interest regions. A budget-constrained coverage selection algorithm is also presented to help network designers choose suitable coverage models to meet the budget and quality requirements. The algorithms are implemented on top of Ns2 and the simulations are carried out using SUMO and OpenStreet Maps. The performance comparison between our algorithm and other two clustering algorithms prove that our algorithm has a better performance in terms of contact time for both sparse coverage and continue coverage.
While the H.264 standard offers improved compression efficiency compared with prior video coding standards, this efficiency arises at the cost of significant complexity. We present a reduced complexity coding algorith...
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While the H.264 standard offers improved compression efficiency compared with prior video coding standards, this efficiency arises at the cost of significant complexity. We present a reduced complexity coding algorithm which estimates, prior to coding each macroblock, whether the coder would choose the skip or code mode for the macroblock. Computation savings are achieved, since pre-coding of skipped macroblocks is avoided. The decision to skip a macroblock is based on estimating and modelling mode cost differences, and employing these models in a MAP framework. Results are shown which indicate that for low-activity sequences savings of over 70% in computation time can be achieved with little or no decrease in video quality.
Data Mining is concerned with the discovery of interesting patterns and knowledge in data repositories. Cluster Analysis which belongs to the core methods of data mining is the process of discovering homogeneous group...
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ISBN:
(纸本)9781467389860
Data Mining is concerned with the discovery of interesting patterns and knowledge in data repositories. Cluster Analysis which belongs to the core methods of data mining is the process of discovering homogeneous groups called clusters. Given a data-set and some measure of similarity between data objects, the goal in most clustering algorithms is maximizing both the homogeneity within each cluster and the heterogeneity between different clusters. In this work, test cases are used to demonstrate that the Euclidean Distance widely in literature is not a suitable metric for capturing the quality of the clustering.
The sea-sky line is an important geographical indication for the detection and tracking of targets on the sea. When a long-range offing target appears, it must be in the sea-sky line area. According to the features of...
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The sea-sky line is an important geographical indication for the detection and tracking of targets on the sea. When a long-range offing target appears, it must be in the sea-sky line area. According to the features of sailing on the sea and six degree-of-freedom movements, an algorithm for realtime position of sea-sky line is proposed. Firstly, the model of the sea camera is constructed. Then according to the projection transformation, the relativity between geographic coordinate system and image coordinate system is derived by means of geometrical deduction. Finally, the mathematical model of sea-sky line is obtained. Experimental results show that the algorithm is accurate, efficient and robust, which lays the foundation for the next visual research of ships.
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