为更全面地对织物表面信息进行表征,方便对织物进行结构分析、外观评估、质量检测和逆向工程等测试,设计了1套可实现数字化图像采集、相机校准和三维重建的纺织品三维轮廓重建方法及系统.自行搭建了1套针对纺织品多角度图像采集平台,同时根据成像参数优化、算法优化深入探讨二者对三维重建效果的影响,逐步优化实验流程和拍摄环境,以提高纺织品三维重建系统的精度.结果表明,在现有硬件的基础条件下,该平台可完成低密度针织物三维轮廓的高精度重建,重建所得模型携带织物表面大量的纹理信息、空间位置关系及颜色信息,特征匹配的特征点均超过1000个.%In order to more fully characterize the surface information of the fabric to facilitate the subsequent fabric structure analysis, appearance evaluation, quality inspection and reverse engineering and other applications,a three-dimensional contour reconstruction method and system were developed for realizing the digital image acquisition,camera calibration and three-dimensional reconstruction. A multi-angle image acquisition platform for textiles was set,the influence of the imaging parameters optimization and the algorithm optimization on the three-dimensional reconstruction effect was investigated, and the experimental process and shooting environment was gradually optimized to improve the system accuracy of the three-dimensional reconstruction of textiles. The results show that based on existing hardware, the platform can complete high-precision reconstruction of the three-dimensional contour of low density textiles,and the reconstructed model can carry a large number of texture information, spatial position relation and color information on the surface of the fabric,and the feature point number is above 1 000.
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