讨论了图象的模糊边缘检测问题。
提出了一种基于模糊边缘检测提取复杂晶界的实用方法。
A practical algorithm based on fuzzy edge detection is proposed.
进而，我们以GVLF构造出广义模糊边缘检测的变换函数。
Further, the transform function for generalized fuzzy edge detection is constructed by GVLF.
最后利用迭代算法对边缘图像进行二值分割。对改进的模糊边缘检测算法进行了实验。
Then a new kind of edge detection operator was used to obtain edges from the enhanced image.
本文结合遥感图像的实际背景，给出了可用于操作实施的模糊边缘检测数学模型和算法。
Conserdering the background of remote sensing image, this paper minutely gives out the fuzzy edge measuring's mathematics models and algorithm which may be used in operating.
这允许我创建某些效果，比如模糊效果或检测边缘，其中过滤的像素颜色取决于它的邻居的颜色。
This would allow me to create certain other effects, such as blurring or edge detection, where the filtered color of the pixel depends on the colors of its neighbors.
结合数学形态学、塔型数据结构及模糊技术，提出一种新的非监督多分辨率边缘检测方法。
A new unsupervised multiresolution edge detection technique was presented, which combines the morphological filtering, pyramid data structure and fuzzy technique.
提出了改进的广义模糊算子(GFO)边缘检测新方法。
A new method for edge detection with improved General Fuzzy Operator (GFO) is proposed.
仿真结果表明：该算法具有较强的检测模糊边缘能力，是一种实用、高效的边缘提取算法，同时此方法很容易扩展到多阈值图像边缘处理。
Simulation results show that: the algorithm is a practical and efficient edge detection algorithm, and this method can easily extend to more threshold edge detection of image processing.
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。
Generalized Fuzzy Operator (GFO) is a new efficient algorithm for edgedetection of an image.
模糊聚类算法(FCM)应用于数字图像的边缘检测已取得了较好的效果。
Fuzzy c-clustering algorithm (FCM) is a useful tool in edge detection of digital image.
本文提出了一种多方向模糊形态学边缘检测算法。
This paper introduces a multi -directions algorithm for image edge detection based on fuzzy mathematical morphology.
为了获取抗噪性强、定位准确的边缘，本文提出了模糊多尺度边缘检测算法。
In order to get anti-noise and good localization image edges, a new fuzzy multi-scale edge detection algorithm is presented in this paper.
图像边缘检测的模糊方法能有效地将物体从背景中区分开来。
Objects can be effectively separated from the background by means of fuzzy math, method which is used to detect the image edge by a computer.
针对传统图像的质量评价测度，提出了一种基于边缘检测的无参考模糊图像评价模型。
Aiming at the traditional image quality assessment metric, this paper put forward a kind of no-reference blurred image assessment model based on edge detection.
自然背景复杂的纹理特征和红外图像中的噪声影响，以及红外目标模糊的边缘，给红外目标的边界检测和分割带来一定的困难。
The effect of natural background and noise in infrared image, fuzzy edge of infrared object, make it difficult to segment and label artificial object in natural background.
基于边缘检测算法确定干涉图中干涉纹的位置来实现干涉相位的解模糊。
First SAR image edge detection techniques are used to find the location of the fringe lines in the interferometric phase image.
本文提出一种首先进行平滑滤波，然后检测模糊边缘的方法来进行复杂景物图像边缘检测。
In the paper, a way of smooth filtering first, then detect edge using fuzzy sets in complex scene image is provided.
针对影像中梯度较小的模糊边缘，提出了一种自适应梯度的概念和边缘检测算法。
A new self-adaptive gradient is proposed for the detection of vague edges which is difficult to be detected according to traditional gradient.
修正后的边缘检测算子在一定程度上克服了边缘的模糊性，提取出更多的细节边缘，又能有效地消除噪声的影响。
The modified edge detection operators can not only overcome the fuzzy of edge to some extent and extract more details of edge, but also effectively eliminate the impact of noise.
而边缘检测提取的模糊方法可克服经典方法的不足，比较适合精细图像边缘的检测和提取；
The fuzzy method for edge detection and extraction, which overcomes the shortcomings of the classic method, is suitable for precision image edge detection and extraction.
模糊技术早已应用于图像边缘检测，但是目前的方法对于复杂景物图像的边缘检测，效果不理想。
Fuzzy method has been used to detect edge, but it is not effective on complex scene image.
本文提出采用数学形态学和线形广义模糊算子相结合的方法检测肿瘤边缘，再根据检测结果得到的肿瘤部位轮廓计算肿瘤大小。
This paper presents a new method, which detects the edge of tumour by adopting mathematical morphology and linear general fuzzy operator.
即使模糊边缘宽度自动检测，也需要您自己确认模糊边缘宽度的正确性。
Even though the Blur Width is auto-detected, you need to satisfy yourself that the Blur Width is correct.
然而，边缘检测又是图像处理中一个困难的问题，因为实际景物图像中的边缘往往是各种类型的边缘以及它们模糊化后结果的组合，实际图像信号存在着噪声。
Because of the noise in the image signal and all kinds of fuzzy edge combined in the image, the edge detection is one of the difficult problem in the image processing.
然而，边缘检测又是图像处理中一个困难的问题，因为实际景物图像中的边缘往往是各种类型的边缘以及它们模糊化后结果的组合，实际图像信号存在着噪声。
Because of the noise in the image signal and all kinds of fuzzy edge combined in the image, the edge detection is one of the difficult problem in the image processing.
应用推荐