A new method for edge detection with improved General Fuzzy Operator (GFO) is proposed.
提出了改进的广义模糊算子(GFO)边缘检测新方法。
Generalized Fuzzy Operator (GFO) is a new efficient algorithm for edgedetection of an image.
广义模糊算子法是一种用于图象边缘检测的全新而有效的方法。
By using of GFO, different display effects of an image can be obtained with different preprocessing methods.
它能与不同的图象预处理方法相结合从而产生不同的图象显示效果。
The algorithm of zero-order Gaussian filtering for an open profile (GFO) was used to correct the edge of the filtered image.
并且利用零阶开环高斯滤波算法，对低通滤波图像的边缘进行了修正。
The GFO employs existing algorithms for the QAP to obtain an initial solution, then applies local search to gain feasibility and optimization.
该算法利用QAP现有算法得到初始解，然后利用局部搜索策略完成解的可行化和优化。
The image templates were firstly processed by Generalized Fuzzy Operator(GFO), then the edge characteristic points obtained by GFS were used as the match points to put some pieces of images together.
应用这些特征点进行眼底图象的配准，最终将各部分眼底图象拼接成一较完整的图象。
The image templates were firstly processed by Generalized Fuzzy Operator(GFO), then the edge characteristic points obtained by GFS were used as the match points to put some pieces of images together.
应用这些特征点进行眼底图象的配准，最终将各部分眼底图象拼接成一较完整的图象。
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