38952395
Efficient Contour Detection Based On Improved Snake Model
Active contour model, also called snake, adapts to edges in an image. A snake is defined as an energy minimizing spline – the snake's energy depends on its shape and location within the image. Problems associated with initialization and poor convergence to boundary concavities, however, have limited its utility. In this paper, we present a new external force field, named gravitation force field, for the snake model. We associate this force field with edge preserving smoothing to drive the snake for solving the problems. Our gravitation force field uses gradient values as particles to construct force field in the whole image. This force field will attract the active contour toward the edge boundary. The locations of the initial contour are very flexible, such that they can be very far away from the objects and can be inside, outside, or the mixture. The improved snake can converge toward the object boundary in a fast pace.
11423295
Multi-view face identification and pose estimation using B-spline interpolation
The available face views in the training set are mostly limited. In this paper, we present a view interpolation method using nonlinear B-spline on face manifolds. Two models, the inner-outer ellipse model and the moment of inertia model, are developed to estimate the pose orientation. We use the limited view-pose face images to form the pose eigen space. Then, based on these nonlinear manifolds we form a B-spline for each individual. Identification is to compute the shortest Euclidean distance from a given test view to the nearest point within one of these B-splines. Once the test view is classified as a familiar individual in the training set, not only can the individual be identified, but also the pose angle can be estimated. Experimental results show that B-spline interpolation can achieve a recognition rate of 95%.
29748731
Support vector machine networks for multi-class classification
The support vector machine (SVM) has recently attracted growing interest in pattern classification due to its competitive performance. It was originally designed for two-class classification, and many researchers have been working on extensions to multiclass. In this paper, we present a new framework that adapts the SVM with neural networks and analyze the source of misclassification in guiding our preprocessing for optimization in multiclass classification. We perform experiments on the ORL database and the results show that our framework can achieve high recognition rates.
207113548
A Hybrid Two-Phase Algorithm For Face Recognition
Scientists have developed numerous classifiers in the pattern recognition field, because applying a single classifier is not very conducive to achieve a high recognition rate on face databases. Problems occur when the images of the same person are classified as one class, while they are in fact different in poses, expressions, or lighting conditions. In this paper, we present a hybrid, two-phase face recognition algorithm to achieve high recognition rates on the FERET data set. The first phase is to compress the large class number database size, whereas the second phase is to perform the decision-making. We investigate a variety of combinations of the feature extraction and pattern classification methods. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Support Vector Machine (SVM) are examined and tested using 700 facial images of different poses from FERET database. Experimental results show that the two combinations, LDA+LDA and LDA+SVM, outperform the other types of combinations. Meanwhile, when classifiers are considered in the two-phase face recognition, it is better to adopt the L1 distance in the first phase and the class mean in the second phase.
16445417
Multiple Viewpoints Based Ontology Integration
Ontology integration is a focus on ontology application field. Ontology can be viewed as a kind of software product. Ontology integration needs to be directed by methodology. In many applications, we need to integrate existed ontologies for a unified ontology for application requirements. The ontology to be integrated can be viewed as a viewpoint of the unified ontology. A multiple-viewpoints-based ontology integration approach is introduced by multiple viewpoints theory in requirement engineering. We define ontology viewpoint by characters of ontology and use conceptual graph to represent semantic in ontology. We discuss the inconsistency checking inner ontology viewpoint and among ontology viewpoints. At last, we use a concept lattice to construct the concept hierarchy.
1936453
A hierarchical refinement algorithm for fully automatic gridding in spotted DNA microarray image processing
Gridding, the first step in spotted DNA microarray image processing, usually requires human intervention to achieve acceptable accuracy. We present a new algorithm for automatic gridding based on hierarchical refinement to improve the efficiency, robustness and reproducibility of microarray data analysis. This algorithm employs morphological reconstruction along with global and local rotation detection, non-parametric optimal thresholding and local fine-tuning without any human intervention. Using synthetic data and real microarray images of different sizes and with different degrees of rotation of subarrays, we demonstrate that this algorithm can detect and compensate for alignment and rotation problems to obtain reliable and robust results.
203662413
The 2nd Order Analysis of IDDQ Test Data
The proposed 2nd order current signature technique considers both the 1st order mean and the 2nd order variance information to provide a more robust and more effective mean of die selection. We examined the IDDQ testing data from SEMATECH by the proposed 2nd order current signature technique and compared the results to those of traditional single threshold and delta-IDDQ techniques. We found that the 2nd order analysis may enable a more robust way to IDDQ testing. In particular, a clear distinction can be made between defected and defect-free dies. The defected dies identified by the proposed technique and by the delta-IDDQ technique are quite similar for the SEMATECH data. However, for the future deep sub-micron VLSI where the mean IDDQ value may vary significantly, the proposed technique has a definite advantage of being more robust.
17724018
Logical structure based semantic relationship extraction from semi-structured documents
Addressed in this paper is the issue of semantic relationship extraction from semi-structured documents. Many research efforts have been made so far on the semantic information extraction. However, much of the previous work focuses on detecting `isolated' semantic information by making use of linguistic analysis or linkage information in web pages and limited research has been done on extracting semantic relationship from the semi-structured documents. In this paper, we propose a method for semantic relationship extraction by using the logical information in the semi-structured document (semi-structured document usually has various types of structure information, e.g. a semi-structured document may be hierarchical laid out). To the best of our knowledge, extracting semantic relationships by using logical information has not been investigated previously. A probabilistic approach has been proposed in the paper. Features used in the probabilistic model have been defined.
13407923
The Application of Two-Dimensional Image Reconstruction for Relics' Preservation and Administration
The purpose of this paper is to build a relics database using for preservation and administration for relics. The paper research on the two-dimensional reconstruction images store in the relics database. The reconstruction images of relics can be used to observe and analyze the antique inside that the eye has no way to distinguish without disruption. This paper have make experiments with six relic samples. By using the industrial computed-tomography (CT) obtain the CT scan data of the six relics samples of different materials and after handling the real data, the experiment and analysis of CT image reconstruction have been carried out. The reconstruction images by SIRT algorithm can clearly indicate the internal structure of the relics. This paper accomplished the comparison of image reconstruction by SIRT algorithm with different iterative relaxation coefficient λ values. This job can provide the CT images data of relics for the relics database. The experiments can provide support for preservation and administration of relics and provide information for teaching and learning activities of cultural studies.
9437535
Practical Application of FDC in Software Service Pricing
This paper proposes a modified fully distributed cost (FDC) pricing method with third-degree price discrimination for software service. The method is a feasible and simple method to be used in practice. The pricing process is generalized as involving data collection, strategy analysis and strategy establishment. Then a practical SCM software service pricing in retail industry is described
11313782
Efficient Heuristics for Solving Probabilistic Interval Algebra Networks
A probabilistic interval algebra (PIA) network is an interval algebra network with probabilities associated with the labels on an edge. The probabilities on each edge sum to 1. A solution is a consistent scenario where the product of the probabilities associated with each unique edge label is maximized. In this paper we investigate previous PIA network solution algorithms, and propose new ones. Our first algorithm is based on best first search and guarantees to output the optimal solution. However, this algorithm is only feasible for toy problems. We augment the algorithm with three heuristics. Although our proposed algorithm does not guarantee an optimal solution, it is very useful in practice. Good solutions can be generated quickly