Ziping Ma

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We extend the linear Radon transform to a nonlinear space and propose a method by applying the nonlinear Radon transform to Zernike moments to extract shape descriptors. These descriptors are obtained by computing Zernike moment on the radial and angular coordinates of the pattern image's nonlinear Radon matrix. Theoretical and experimental results validate(More)
In this paper we propose a novel visual method for protein model classification and retrieval. Different from the conventional methods, the key idea of the proposed method is to extract image features of proteins and measure the visual similarity between proteins. Firstly, the multiview images are captured by vertices and planes of a given octahedron(More)
—In this paper we propose a novel approach called three feature functions based on Radon transform directly. The corresponding features are defined as the symmetry of the shape, the width of contour, the fullness of the shape. They reveal the information of visual and the inner structures of shape using characteristics of Radon projective space. Theoretical(More)
In this paper a new algorithm is proposed based on multiple feature and particle swarm optimization for target tracking. The multiple feature includes local binary pattern (LBP) ,phase congruent (PC) and gradient magnitude(GM). This method not only can make use of contrast invariance of phase congruent, but also can fully utilize the rotation invariance of(More)
In order to reduce the computation cost of extracting feature, a new algorithm for image retrieval is proposed. This method utilize multiple-feature including ellipse measuring as shape feature, phase congruent and gradient magnitude as the contrast feature for image retrieval in this paper. It not only can fill up a deficiency of the contrast invariant of(More)
Various types of orthogonal moments have been widely used for object recognition and classification. In the paper, a new set of the rotation and scale invariants of Legendre moments is introduced. In order to achieve good results in CBIR experiments and image classification experiments using the rotation and scale invariants of Legendre moments, we(More)
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