The fast computation of Zernike moments from normalized geometric moments has been developed in this paper. The computation is multiplication free and only additions are needed to generate Zernike moments. Geometric m...
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The fast computation of Zernike moments from normalized geometric moments has been developed in this paper. The computation is multiplication free and only additions are needed to generate Zernike moments. Geometric moments are generated using Hatamian's filter up to high orders by a very simple and straightforward computation scheme. Other kinds of moments (e.g., Legendre, pseudo Zernike) can be computed using the same algorithm after giving the proper transformations that state their relations to geometric moments. Proper normalizations of geometric moments are necessary so that the method can be used in the efficient computation of Zernike moments. To ensure fair comparisons, recursive algorithms are used to generate Zernike polynomials and other coefficients. The computational complexity model and test programs show that the speed-up factor of the proposed algorithm is superior with respect to other fast and/or direct computations. It perhaps is the first time that Zernike moments can be computed in real time rates, which encourages the use of Zernike momentfeatures in different image retrieval systems that support huge databases such as the XM experimental model stated for the MPEG-7 experimental core. It is concluded that choosing direct computation would be impractical.
A new method for natural color image segmentation using integrated mechanism is proposed in this paper. Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to ...
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A new method for natural color image segmentation using integrated mechanism is proposed in this paper. Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to label long edge lines based on the global color information to estimate roughly the distribution of objects in the image, while short ones are merged based on their positions and local color differences to eliminate the negative affection caused by texture or other trivial features in image. Region growing technique is employed to achieve final segmentation results. The proposed method unifies edges, whole and local color distributions, as well as spatial information to solve the natural image segmentation problem. The feasibility and effectiveness of this method have been demonstrated by various experiments.
A new method to reconstruct 3D scene points from nonparallel stereo is proposed. From a pair of conjugate images in an arbitrarily configured stereo system that has been calibrated, coordinates of 3D scene points can ...
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A new method to reconstruct 3D scene points from nonparallel stereo is proposed. From a pair of conjugate images in an arbitrarily configured stereo system that has been calibrated, coordinates of 3D scene points can be computed directly using the method, bypassing the process of rectifying images or iterative solution involved in existing methods. Experiment results from both simulated data and real images validate the method. Practical application to surgical navigator shows that the method has advantages to improve efficiency and accuracy of 3D reconstruction from nonparallel stereo system in comparison with the conventional method that employs algorithm for standard parallel axes stereo geometry.
Pace recognition subjected to various conditions is a challenging task. This paper presents a combined feature improved Fisher classifier method for face recognition. Both of the facial holistic information and local ...
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Pace recognition subjected to various conditions is a challenging task. This paper presents a combined feature improved Fisher classifier method for face recognition. Both of the facial holistic information and local information are used for face representation. In addition, the improved linear discriminant analysis (I-LDA) is employed for good generalization capability. Experiments show that the method is not only robust to moderate changes of illumination, pose and facial expression but also superior to the traditional methods, such as eigenfaces and Fisherfaces.
Face recognition has attracted great interest due to its importance in many real-world applications. In this paper,we present a novel low-rank sparse representation-based classification(LRSRC) method for robust face r...
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Face recognition has attracted great interest due to its importance in many real-world applications. In this paper,we present a novel low-rank sparse representation-based classification(LRSRC) method for robust face recognition. Given a set of test samples, LRSRC seeks the lowest-rank and sparsest representation matrix over all training samples. Since low-rank model can reveal the subspace structures of data while sparsity helps to recognize the data class, the obtained test sample representations are both representative and discriminative. Using the representation vector of a test sample, LRSRC classifies the test sample into the class which generates minimal reconstruction error. Experimental results on several face image databases show the effectiveness and robustness of LRSRC in face imagerecognition.
Effects of the speed relaxation time on the optimal velocity car-following model (OVM) with delay time due to driver reaction time proposed by Bando et al.(1995) were studied by numerical methods. Results showed that ...
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Effects of the speed relaxation time on the optimal velocity car-following model (OVM) with delay time due to driver reaction time proposed by Bando et al.(1995) were studied by numerical methods. Results showed that the OVM including the delay is not physically sensitive to the speed relaxation times. A modified car-following model is proposed to overcome the deficiency. Analyses of the linear stability of the modified model were conducted. It is shown that coexisting flows appear if the initial homogeneous headway of the traffic flow is between critical values. In addition, phase transitions occur on varying the initially homogeneous headway.
Given a smooth surface that is z-axis symmetric, illuminated in an arbitrary direction and fully contained within the field of view, it is proven that shape-from-shading is uniquely determined by using a polar coordin...
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Given a smooth surface that is z-axis symmetric, illuminated in an arbitrary direction and fully contained within the field of view, it is proven that shape-from-shading is uniquely determined by using a polar coordinate system and a Fourier expansion.
A new model-based speech enhancement algorithm by variational Bayesian learning was proposed in this paper. Autoregressive process was used to model speech signal and its order was determined automatically. Clean spee...
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A new model-based speech enhancement algorithm by variational Bayesian learning was proposed in this paper. Autoregressive process was used to model speech signal and its order was determined automatically. Clean speech signal could be estimated using a variational Kalman smoother. Moreover, overfitting was avoided in the learning of model parameter and model structure. Experimental results compared with Kalman filter-based enhancement and spectral subtraction methods demonstrate the performance of our algorithm.
An additive discussion for the validity of using the weighted information entropy to evaluate the complex degree of infrared （IR） backgronnds is given, Since small targets can be temporarily lost in actual infrared ...
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An additive discussion for the validity of using the weighted information entropy to evaluate the complex degree of infrared （IR） backgronnds is given, Since small targets can be temporarily lost in actual infrared video sequences, an adaptive binarization threshold for small targets detection is presented. Experimental results show the robustness of our method,
A method is presented for computing the pose of rigid 3D objects with arbitrary curved surfaces. Given an input image and a candidate object model and aspect, the method will verify whether or not the object is presen...
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A method is presented for computing the pose of rigid 3D objects with arbitrary curved surfaces. Given an input image and a candidate object model and aspect, the method will verify whether or not the object is present acid if so, report pose parameters. The curvature method of Basri and Ullman is used to model points on the object rim, while stereo matching is used for internal edge points. The model allows an object edgemap to be predicted from pose parameters. Pose is computed via an iterative search for the best pose parameters. Heuristics are used so that matching can succeed in the presence of occlusion and artifact and without resorting to use of corresponding salient feature points. Bench tests and simulations show that the method almost always converges to ground truth pose parameters for a variety of objects and for a broad set of starting parameters in the same aspect.
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