The process of image treatment is as follow: filter, enhance, making binary image by adaptive threshold, edge detection and so on.
本文所采用的图像处理主要步骤为：滤波、增强、自适应阈值二值化、边缘提取等预处理。
In preprocessing, optimal threshold value method and smooth technology are adopted to process sample form image.
预处理阶段，使用最佳阈值二值化方法和平滑技术处理样本表格图像。
But after the Gauss filter process, the threshold image is changed into smooth one which has smaller burr and has better connectedness.
提出一种“高斯滤波”的方法去除这些白点，使二值化图像平滑、少毛刺，并具有较好的连通性。
To get a clear weld image, iterative threshold method is developed to process the image binary.
采用迭代的阀值化方法对图像进行二值处理，可以获得清晰的焊缝图像。
The real-time measuring is achieved by adopting some fast image process algorithm such as image tower, feature abstraction and adaptive image threshold.
通过采用图像分层、特征提取和自适应阈值分割等快速图像处理方法实现了对模型迎角的实时测量。
Image segmentation technique is the key process from image processing to image analysis. It is difficult to choose multi-threshold precisely and automatic using the basic image segmentation technique.
图像分割技术是图像处理到图像分析的关键步骤，应用基本的分割技术很难达到多阈值的自适应精确选取。
The traditional OTSU threshold method has been improved in order to establish a good foundation for feature extraction and the fitting of 3D in image process with calibration plate.
本文利用改进的OTSU阈值方法测量人体空间三维尺寸的带标定框图像，为后续的特征点提取和三维拟合计算打下良好的基础。
The traditional OTSU threshold method has been improved in order to establish a good foundation for feature extraction and the fitting of 3D in image process with calibration plate.
本文利用改进的OTSU阈值方法测量人体空间三维尺寸的带标定框图像，为后续的特征点提取和三维拟合计算打下良好的基础。
应用推荐