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In this paper, we investigate the use of discriminant feature selection techniques in the elastic graph matching (EGM) algorithm. State of the art and novel discriminant dimensionality reduction techniques are used in the node feature vectors in order to extract discriminant features. We illustrate the improvements in performance in frontal face verification using a modified multiscale morphological...
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...
This paper presents a new method for texture based image retrieval. The proposed algorithm uses a periodically extended variant of the curvelet transform. The sum of the absolute value of differences in the mean and standard deviation between curvelet wedges representing the query image and the test image is used as the distance index. Performance improvement is demonstrated using the CUReT database,...
Several existing content-based image retrieval and classification systems rely on low-level features which are automatically extracted from images. However, often these features lack the discrimination power needed for accurate description of the image content and hence they may lead to a poor retrieval or classification performance. This article applies an evolutionary feature synthesis method based...
This paper presents a predictive model for the prediction and modeling of nonlinear, chaotic, and non-stationary electrocardiogram signals. The model is based on the combined usage of Hilbert-Huang transform, False nearest neighbors, and a novel neural network architecture. This model is intended to increase the prediction accuracy by applying the Empirical Mode Decomposition over a signal, and to...
In this paper, we propose a novel approach SDR-CS (Sparse Dimensionality Reduction based on CS) based on compressed sensing to reduce dimensionality. With certain constraint of objective function, our semi-supervised learning method utilizes instance to construct the optimally sparse dictionary in the training dataset, employs K-SVD and OMP algorithms to improve the convergence rate of learning, and...
Planetary surface science operations performed by robotic space systems frequently require pointing cameras at various objects and moving a robotic arm end effector tool toward specific targets. Earlier NASA Mars Exploration Rovers did not have the ability to compute actual coordinates for given object coordinate frame names and had to be provided with explicit coordinates. Since it sometimes takes...
This paper presents a new method to automatically locate pupils in images (even with low-resolution) containing human faces. In particular pupils are localized by a two steps procedure: at first self-similarity information is extracted by considering the appearance variability of local regions and then they are combined with an estimator of circular shapes based on a modified version of the Circular...
The FM (Frame Manager) flight software module is responsible for maintaining the frame tree database containing coordinate transforms between frames. The frame tree is a proper tree structure of directed links, consisting of surface and rover subtrees. Actual frame transforms are updated by their owner. FM updates site and saved frames for the surface tree. As the rover drives to a new area, a new...
In this paper we propose a novel method for shape analysis called HTS (Hough Transform Statistics), which uses statistics from Hough Transform space in order to characterize the shape of objects in digital images. Experimental results showed that the HTS descriptor is robust and presents better accuracy than some traditional shape description methods. Furthermore, HTS algorithm has linear complexity,...
A novel curved surface representation which is relatively invariant under the transformations of the 3D motion group is introduced in this paper. It is computed from the superposition of the two geodesic potentials generated from a given couple of surface points. By considering a levels set of such geodesic potentials, finite invariant points are obtained. Two numerical methods are implemented and...
Paper presents performance comparison of palm print identification techniques based on fractional coefficients of transformed palm print edge image using three transforms namely Cosine., Haar and Kekre. In transform domain., the energy of image gets concentrated towards low frequency region; this characteristic of image transforms is used here to reduce the feature vector size of palm print images...
Automatic personal identification is playing an important role in security systems. Biometrics technologies has been emerging as a new and effective methods to achieve accurate and reliable identification results. A number of biometric traits exist and are in use in various applications. Palmprint is one of the relatively new biometrics due to its stable and unique characteristics. In this paper,...
Concatenative speech synthesis (CSS) provides the greatest naturalness. However, it requires a huge stored database resulting a huge footprint. Reducing the capacity of stored database while preserving the quality of CSS, or improving the quality to size ratio (QSr), is still a challenge. In this paper, we propose a method of transforming fundamental frequency (F0) contours of lexical tones, developed...
The discriminative common vectors (DCV) algorithm shows better face recognition effects than some commonly used linear discriminant algorithms, which uses the subspace methods and the Gram-Schmidt orthogonalization (GSO) procedure to obtain the DCV. However, the Gram-Schmidt technique may produce a set of vectors which is far from orthogonal so that sometimes the orthogonality may be lost completely...
The rapid increase in the usage of Location Based Services (LBS) due to the rise of the smartphone is focusing attention on how applications are accessing users' context location. Smartphone operating systems such as iOS and Android currently promote a "one size fits all" approach and do not discriminate between services on the accuracy and extent of location disclosure. A general lack of...
Feature extraction is one of the most important problems in image recognition tasks. In many applications such as face recognition, it is desirable to eliminate the redundancy among the extracted discriminant features. In this paper, we propose two novel feature extraction approaches named local uncorrelated discriminant transform (LUDT) and weighted global uncorrelated discriminant transform (WGUDT)...
The Partial Least Squares(PLS) is a novel multivariate data analysis method developed from practical applications in real world. It is not influenced by the total scatter matrices of training samples being singular or not. So PLS can efficiently deal with the case of high-dimensional space with only small sample size such as biological feature recognition. The standard PLS firstly reshapes images...
A new feature description is used for human behaviour representation and recognition. The feature is based on Radon transforms of extracted silhouettes. Key postures are selected based on the Radon transform. Key postures are combined to construct an action template for each sequence. Linear discriminant analysis (LDA) is applied to the set of key postures to obtain low dimensional feature vectors...
Recently, locality sensitive discriminant analysis (LSDA) was proposed for dimensionality reduction. As far as matrix data, such as images, they are often vectorized for LSDA algorithm to find the intrinsic manifold structure. Such a matrix-to-vector transform may cause the loss of some structural information residing in original 2D images. Firstly, this paper proposes an algorithm named two-dimensional...
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