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In this paper, we improved the method of minimum squared error for robust classification by altering its classification rule. The minimum squared error method, is one of the methods to minimize the sum of the squared error between the output of the linear function and the desired output, which first obtains the mapping that can best transform the training sample into its class label and then exploits...
A fast image stitching algorithm based on improved speeded up robust feature (SURF) is proposed to overcome the real-time performance and robustness of the original SURF based stitching algorithms. The machine learning method is adopted to build a binary classifier, which identify the key feature points extracted by SURF and remove the non-key feature points. In addition, the RELIEF-F algorithm is...
Selecting a feature subset with strong discriminative power is a critical process for high dimensional data analysis, which has attracted much attention in many application domains, such as text categorization and genome projects. Since traditional feature selection methods provide limited contributions to classification, many researchers resort to hybrid or elaborate approaches to choose interesting...
The Gaussian Mixture Modeling (GMM) algorithm with connected component labeling as object extraction provide robust background subtraction but suffer from complexity, and large buffer or high bandwidth due to the frame level operations. For real time application needs, this paper proposed a block based GMM design for background subtraction with message passing between blocks to avoid performance drop...
Designing consensus function by analyzing ensemble method of clustering members and clustering, then the class center will be determined by the way of using the weighted method. Clustering ensemble, which is Based on part priority clustering algorithm, is to improve the accuracy of the algorithm. Experiments results proved that the algorithm which is optimized takes great advantages over that in scalability,...
The attacks such as Denial of Service (DoS) violate the security of Network-on-Chip (NoC) which emerges as a promising solution for multi-core system. In this paper, we explore the robustness of mesh-based NoC architecture under various flooding-based DoS attacks. Simulation results reveal that the robustness of NoC architecture can be correlated with parameters such as routing algorithm, the number...
The need for secure communications has significantly increased with the explosive growth of the internet and mobile communications. The usage of text documents has doubled several times over the past years especially with mobile devices. In this paper, we propose a new steganography algorithm for Unicode language (Arabic). The algorithm employs some Arabic language characteristics which represent...
Understanding an individual's contribution to an ecosystem often necessitates integrating information from multiple repositories corresponding to different projects within the ecosystem or different kinds of repositories (e.g., mail archives and version control systems). However, recognising that different contributions belong to the same contributor is challenging, since developers may use different...
A main challenge associated with 3-dimentional fringe pattern profilometry (3D-FPP) systems is the unwrapping of phase maps resulted from complex object surface shapes with both robustness and speed guaranteed. In this paper we propose a new quality-guided phase unwrapping algorithm. In contrast to the conventional quality-guided methods, we classify pixels on wrapped phase map into two types by detecting...
Self-labeled training data in semi-supervised learning may contain much noise due to the initial insufficient training data, which may hurt the generalization ability of the final hypothesis. In this paper, we propose an Active Semi-Supervised framework with Data Editing(ASSDE) to improve sparsely labeled text classification. A data editing technique is used to identify and remove noise introduced...
For detecting multiple planar regions rapidly in the image sequence, this paper proposed a novel algorithm. First of all, the method uses RANSAC to detect a dominant homography, then, the method calculates the poles corresponding to the two images based on homography constraint and classify all the matching feature points. When detect the homography corresponding to more planes based on RANSAC once...
Background subtraction is very important part of surveillance applications for successful segmentation of objects from video sequences. The robust initial background extraction is crucial in any background subtraction. In this paper, we propose an algorithm to extract initial background from surveillance videos using dual frame differences and morphological processing. With the proposed algorithm,...
A classification scheme for content-based audio signal retrieval is proposed in this paper. The proposed scheme uses the Centroid Neural Networks (CNN) with a Divergence Measure called Divergence-based Centroid Neural Network (DCNN) to perform clustering of Gaussian Probability Density Function (GPDF) data. In comparison with other conventional algorithms, the DCNN designed for probability data has...
The aim of this paper is to present a new robust feature extraction method. Our method is an extension of the classical Partial Least Squares (PLS) algorithm. However, a robust approach and new weighted separation criterion is applied. This algorithm based on Minimum Covariance Determinant (MCD) approach and new separation criterion called Weighted Criterion of Difference Scatter Matrices (WCDSM)...
In order to improve security of DWT-based information hiding algorithm, this paper introduces an information hiding algorithm based on DWT with alterable parameters, in which the parameters are used to be key to control the locations of embedding secret messages. Embedding signals disperse in domain guessed by attacker, and which makes attacker difficult to steganalyze. Analysis and experiment results...
Text data in an image present useful information for annotation, indexing and structuring of images. The gathered information from images can be applied for devices for impaired people, navigation, tourist assistance or georeferencing business. In this paper we propose a novel algorithm for text detection and localization from outdoor/indoor images which is robust against different font size, style,...
For the limited application and shortcoming of FCM (Fuzzy C-Means) clustering algorithm, an improved automatic FCM clustering algorithm is put forward. First, the fuzzy equivalent matrix is achieved by fuzzier the standard uniform data sets; then, the objective function of the improved automatic FCM clustering algorithm is optimized by the amendment of membership function and distance measuring function;...
A novel Hybrid Clustering Algorithm (HCA) that incorporates the K-means into the canonical Immune Programming Algorithm (IPA) is proposed after analyzing the advantages and disadvantages of the classical k-means clustering algorithm in the paper. The theory analysis and experimental results show the algorithm not only avoids the local optima and is robust to initialization, but also increases the...
The fax clustering is that the same or similar faxes will be clustered into one group in mass faxes. In order to improve accuracy of clustering, a fax clustering algorithm based on adaptive ant colony optimization was proposed in this paper. The algorithm simulates ant feeding theory, and improves the coefficient of pheromone updating, and avoids falling into local optimum. The experimental results...
According to the comprehensive analysis of the traditional DV-Hop, we propose an Iterative Cooperation DV-Hop localization (ICDV-Hop) algorithm, which improves the localization performance through adopting hop count threshold, collinearity test and new beacon nomination. The proposed algorithm selects the optimal beacon nodes for high localization accuracy by employing the hop count threshold to limit...
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