This paper proposed a method for fabric defects edge detection based on discrete stationary wavelet transform (DSWT) and optimal threshold segmentation algorithm (OTSA).
文章提出了基于离散平稳小波变换和最佳阈值分割算法的织物疵点边缘检测方法。
In image segmentation algorithms, the selection of optimal threshold is the key to segmentation.
在阈值分割算法中，确定最优阈值是图像分割的关键。
Based on prior information, the optimal segmentation threshold will be determined for initial segmentation.
基于先验信息从初始分割阈值中确定最佳分割阈值并进行初步分割。
Finally, the output of this algorithm is the optimal threshold. Using this threshold to partition off the pixels, image segmentation is implemented.
最后，通过寻优搜索得到算法的输出值即为最优阈值，以此阈值划分像素，实现图像分割。
The experimental result shows that this method is effective in calculating the optimal segmentation threshold of an image.
实验结果表明，该方法是求解多峰值直方图图像的最优分割阈值的有效手段。
Firstly, a rough motion mask is obtained by introducing a motion area segmentation method based on an improved accumulative frame- difference algorithm and optimal threshold segmentation.
利用小波包分析算法提取出单帧图像的边缘信息并获得细化的目标区域边缘图；
Firstly, a rough motion mask is obtained by introducing a motion area segmentation method based on an improved accumulative frame- difference algorithm and optimal threshold segmentation.
利用小波包分析算法提取出单帧图像的边缘信息并获得细化的目标区域边缘图；
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