In image segmentation, threshold selection is very important.
在图像分割中，阈值的选取至关重要。
Thresholding methods are usual and efficient in image segmentation.
阈值分割是图像分割中的一种常用的有效方法。
There are many successful fuzzy set theory methods in image segmentation.
目前模糊集理论在图像分割中的应用有许多成功的方法。
Multiple-objects contour extraction is an important area in image segmentation.
多目标轮廓提取是图像分割的重要研究内容。
Markov random field method is a very active research field in image segmentation.
马尔可夫随机场方法是图像分割中一个极为活跃的研究方向。
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。
Fuzzy clustering is an important branch of fuzzy set theory, and is widely applied in image segmentation.
模糊聚类是模糊理论的一个重要的分支，在图像分割中得到广泛应用。
The geodesic active contour model has been wide used in image segmentation for its computational stability.
几何活动轮廓模型以其计算稳定等优点，被广泛用于图像分割。
In this paper, the application of suppressed fuzzy clustering algorithm in image segmentation is introduced.
本文给出了模糊聚类算法在图像分割中的应用结果。
The experiment shows that it can receive satisfactory results using Quadtree techniques in image segmentation.
实验表明，把四叉树结构引入图像分割，收到了较好的效果。
Level Set methods are robust and efficient numerical tools for resolving curve evolution in image segmentation.
水平集方法应用于图象分割的曲线或曲面进化问题，是一种稳定有效的数值计算方法。
Deformable model is playing a more and more important role in image segmentation owing to its unique advantages.
形变模型凭借其独特的优势，在图像分割领域得到了越来越广泛地研究和应用。
Second, the method of constructing fuzzy membership function is proposed in image segmentation based on fuzzy mutual information.
其次将模糊互信息量用于图像分割时给出具体隶属度函数的构造；
In image segmentation for engineering applications, the requirements of efficiency, integrity, accuracy, stability must be satisfied.
适合于工程应用的图像分割技术必须满足有效、整体、精确、稳定等一系列要求。
Geometric properties, such as perimeter and connected component, have been widely used in image segmentation and pattern recognition.
图像的几何性质，比如区域周长和连通分量，在图像分割和模式识别领域得到了广泛的应用。
In this paper, a two-stage search fast algorithm for adaptive projective decomposition, which is used in image segmentation, is presented.
针对应用于图像分割的自适应正交投影分解方法的具体算法的实现问题，提出了一种基于两阶段搜索的实现算法。
This paper proposes a new region based segmentation method based on cloud model in order to take uncertainty into account in image segmentation.
针对区域分割方法中存在的不确定性问题，提出了一种基于云模型的区域分割方法。
Suppressing noise is the difficult problem in image segmentation, so we have study suppressing noise in multiresolution segmentation based on Wavelet transform.
噪声的存在是图像分割的困难所在，本文着重研究了基于小波变换的多分辨率分割中噪声抑制的问题。
To determine the optimal thresholds in image segmentation, a new multilevel thresholding method based on particle swarm optimization (PSO) is proposed in this paper.
为确定图像分割的最佳阈值，基于粒子群优化算法提出了一种多阈值图像分割方法。
The most basic principle in image segmentation is to determine the threshold, and use it to divide different pixel into different categories, to achieve image segmentation.
图像分割的最基本的原理是确定阈值，并由阈值将图像中的不同像素归为不同的类别，完成图像的分割。
Medical image segmentation is a classic problem in image segmentation field, because of the complexity of medical images, so far there is not any all-purpose segmentation method.
医学图像分割是图像分割领域的一个经典问题，由于医学图像的复杂性，到目前为止还不存在一个通用的分割方法。
With high computing complexity, traditional 2-d maximum entropy method is a defective method in image segmentation, although many algorithms have been proposed to bear on this problem.
图像分割二维最大熵算法存在计算复杂度高的弊端，目前针对这个问题所提出的各类算法效果都不太理想。
Image thresholding segmentation method based on fuzzy partition entropy has good segmentation performance and becomes a kind of extensive application method in image segmentation field.
基于模糊划分熵的图像阈值化分割方法因具有良好的分割性能已成为图像分割广泛应用的方法之一。
This paper researches qualitative and quantitative transformation model-cloud model in uncertain artificial intelligence in order to solve uncertain questions which exist in image segmentation.
论文针对图像分割中存在的不确定性问题，通过研究不确定性人工智能中定性和定量的转换模型—云模型，提出一种新的基于云模型的图像分割方法。
“Three-D reconstruction, massive-scale image segmentation …” he says. “People can do these things in almost real time now.”
“三维重建、大规模图像分割……”，他说，“人们现在甚至可以实时完成这些工作。”
Image segmentation is one of key issues in Computer Vision.
图像分割是计算机视觉中的关键步骤之一。
Image segmentation is one of the most basic areas in image processing.
图像分割是图像处理中最为基础的领域之一。
Image segmentation is one of the most basic areas in image processing.
图像分割是图像处理中最为基础的领域之一。
应用推荐