基于显微光学切片方法的织物绒毛深度信息获取

Obtaining of Depth Information of Fuzzes Based on the Optical Sectioning Microscopy

在织物绒毛的自动检测中,深度信息是使毛球与织物表面分离的关键信息。基于"显微光学切片"的思想,通过显微镜采集织物表层的同轴序列多焦面图像,并利用聚焦程度获取织物表层各点的深度信息。将序列图层经去噪平滑处理之后,沿图层深度方向搜索各平面点(x,y)的成像最清晰位置z,投影至灰度空间之后建立织物表面及绒毛的深度图像。提出了新的清晰度评价标准——基于自适应区域选择的梯度方差算法,并将此方法与3种传统清晰度评价标准进行比较。试验结果表明,提出的新方法不仅能正确测量像素点清晰度,而且抗噪能力较强。

The depth information of fabric surface is a key parameter for segmenting pills from fabric surface. The idea of ＂optical sectioning microscopy＂ was adopted, allowing the system to obtain the depth information of fabric surface by focusing at each point under microscope. The sequential layers of fabric images were captured under the microscopy at different focal position. Then after image denoising, the depth value z for each plain position（x,y） was obtained by finding the layer with maximum sharpness. The depth data of fabric surface was projected to gray space, and a depth map was formed. A new clarity-evaluation method based on variance of gradient within adaptive local region was put forward. Compared with three traditional clarity-evaluation indexes, the method was proved to be accurate and less noise-sensitive.