Yongmei Michelle Wang

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We propose a unified framework for boundary finding, where a Bayesian formulation, based on prior knowledge and the edge information of the input image (likelihood), is employed. The prior knowledge in our framework is based on principal component analysis of four different covariance matrices corresponding to independence, smoothness, statistical shape and(More)
Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning Support Vector Machines (SVMs) are used in our(More)
We propose an approach for boundary finding where the correspondence of a subset of boundary points to a model is simultaneously determined. Global shape parameters derived from the statistical variation of object boundary points in a training set are used to model the object. A Bayesian formulation, based on this prior knowledge and the edge information of(More)
This paper describes two new atlas-based methods of 2D single modality non-rigid registration using the combined power of physical and statistical shape models. The transformations are constrained to be consistent with the physical properties of deformable elastic solids in the first method and those of viscous fluids in the second, to maintain smoothness(More)
This paper describes a new method for determining correspondence between points on pairs of surfaces based on shape using a combination of geodesic distance and surface curvature. An initial sparse set of corresponding points are generated using a shapebased matching procedure. Geodesic interpolation is employed in order to capture the complex surface. In(More)
The non-rigid registration of surfaces is a complex and difficult task for which there are many important applications, such as comparing shape between deformable objects and comparing associated function. This paper presents a new approach for brain surface matching by determining the correspondence of 3D point sets between pairs of surfaces. The algorithm(More)
This paper describes a new method of non-rigid registration using the combined power of elastic and statistical shape models. The transformations are constrained to be consistent with a physical model of elasticity to maintain smoothness and continuity. A Bayesian formulation, based on this model, on an intensity similarity measure, and on statistical shape(More)
The structural characteristics and component differences of proanthocyanidins in brown and white cotton fibres were identified by nuclear magnetic resonance (NMR) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) analyses. Proanthocyanidins in brown and white cotton fibres were found to contain mainly(More)
Phenolic compounds are present at very high concentrations in the bark of Acacia mangium. These compounds are known to have strong antioxidant activity and thus different beneficial effects on human health. Phenolic compounds in bark of A. mangium were extracted and their antioxidant activities were investigated using the 1,1-diphenyl-2-picrylhydrazyl(More)