关键词: 数据点云, 特征提取, 多尺度几何分析, Curvelet变换

Abstract: The current surface feature extraction method has limitations for multi directions analysis of data point. Curvelet transform is introduced to analysis of data point to research on surface feature extraction method. Second-generation discrete curvelet transform is used to analyze data point based on slicing and expanding preprocessing data point. Curvelet transform coefficients of detail layer and fine layer present the edge and contour of data point. Compromise for soft and hard thresholds is used to process curvelet transform coefficients of Detail layer and Fine layer to enhannce the edge and contour of data point. The data point is reconstructed from the enhanced Curvelet transform coefficient with Curvelet inverse transformation. Boundary contour is achieved to extract surface feature. Surface feature is achieved by extrcating the edge and contour of data point. A surface feature extraction method is proposed based on Curvelet transform. Example shows the proposed method can accurately extract surface feature from data point.

Key words: data point, feature extraction, multi-scale geometric analysis, Curvelet transform