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已收藏
¥{[getMoney(5000)]}
预算
7
天计划工期
{[ job.pattern_id != 9 ? '项目详情' : '职位详情']}
由于目前常见SFIT及SURF对于口腔内窥镜应用于牙齿图片的拼接存在不足(光线较暗、距离近、点位少、图片的转动)
该论文所提方法可以显著改善拼接效果:
we propose an approach to improve the matching in these low-texture regions. First, normals of tooth surface is extracted using a shape from shading. Due to the oral environment, the surface normals impact many of imprecise values; hence we formulate an algorithm to rectify these values and generate normal maps. The normal maps reveals the impacted geometric properties of the images inside an area, boundary, and shape. Second, the normal maps are used to detect, extract and match the corresponding features. Finally, to enhance the stitching process for these unidealized data, normal maps are used to estimate as-projective-as-possible warps. The proposed approach outperforms the state-of-the-art auto-stitching approach and shows a better performance in such cases of low-texture regions.
需达到不低于论文效果的全景拼接图片(牙齿闭合正面一张,分开是上下咬合面及背面两张)
需详细说明算法原理
在完成论文所述算法后,需配合对实际硬件进行匹配完善
请先进行基本代码实验后再报名
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