象其他的热点区域一样，包括撒丁岛和冰岛，冲绳是一个相对封闭的岛屿社区，其导致了很高程度的近亲繁殖和遗传性变形聚类。
Like other hotspots, including Sardinia and Iceland, Okinawa is a relatively isolated island community, which leads to higher levels of inbreeding and a clustering of genetic variants.
然后在MTM系统中，利用颜色密度聚类的方法得到区域颜色的特征。
And then in MTM system, we get region color features from the proposed color density-based clustering.
在车牌定位阶段，本文提出了基于连通区域水平聚类的车牌粗定位方法。
At the license plate location phase, we propose a new rough localization method which based on connected area horizontal clustering.
该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。
It can handle spatial data and spot any-shape clusters in a noised spatial database by dividing them into clusters with high enough density.
利用Z曲线聚类和降维特性，本文给出网格划分方法、搜索区域分解过程，提出一种高维空间范围查询算法。
Based on Z curve, the paper presents a method of grid partition, a procedure of partitioning search region, and a high-dimensional spatial range query algorithm.
提出了利用人体区域彩色聚类和人体运动的相关知识，理解机器视觉中人体运动的方法。
An approach of using human region color clustering and human motion knowledge to understand human motion in machine vision is introduced.
找出不同区域的有效的参量组合结构，判断后续聚类结构，对未来地震大小做出预测。
Found the best parameters' combination structure of different regions, determined the latter clustering structure, and predicted the future earthquakes magnitude.
首先，运用K-均值聚类方法提取出细胞核，并且采用多域值分割演算法去除细胞图像中的背景区域。
Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation.
第二种方法是基于时差分模糊熵聚类的运动变化区域检测算法。
Other way is the motion-changed region detection algorithm based on fuzzy entropy clustering in time-differenced image .
将灰色聚类理论应用于珠江三角洲区域稳定性分区评价，建立了灰色系统数学模型。
Grey system theory has been firstly applied to the zoning evaluation on regional stability of the Pearl River Delta, and a mathematical model of grey system has been established in this paper.
根据粗糙集理论的边界区域和V -支持向量机的优点对支持向量聚类算法进行改进。
According to the border region of rough set theory and the merits of V-support vector machine, the algorithm of support vector clustering is improved.
通过在类的边界区域进行细化来提高网格划分的质量从而提高聚类的精度。
It improves the quality of grid partition by refining the edge of the class, so improves the quality of the clustering.
基于数学形态学的方法，研究了两种针对这种较复杂情况的成熟草莓果实分割的方法，即聚类快速分割法和分水岭区域分割法。
Based on the mathematical morphological algorithm, two methods to solve this complexity were proposed, namely, Clustering Fast Segmentation and Watershed Region Segmentation.
本文论述了目前有关泥石流危险度分区的两种主要方法：区域泥石流危险度分区法和多元聚类分区法。
This paper has discussed the two main methods of regionalization of debris flow risk degree at present, that is, by regional debris flow risk degree and by multivariate collection analysis.
本文认为其原因是我国区域在梯度推移过程中存在着粘性，并分别建立简单的粘性模型和灰色聚类粘性模型进行分析。
The author attributes the phenomena to the stickiness in the economic gradient process and sets up simple stickiness model and grey clustering model to explain it.
最后考虑到像素空间的区域连续性，在颜色聚类结果的基础上进行区域生长。
Finally, considering the consecution of the district of the pixel space, on the basis of the result of color clustering, the region-growing is wanted to be processing.
从本质上讲，纹理聚类的任务是根据图像中各像素所处的不同区域，将它们归至未知的不同类别。
In essence, texture clustering is equal to classify different texture pictures to unknown classes on basis of pixels of an image belonging to different regions.
本文提出的基于连通组件的文字定位方法可以非常好地定位出图像中的显著文字区域，但是由于聚类和使用的特征不够完善，不能定位与背景色相近或者是倾斜的文字。
The proposed method is able to locate obvious text areas in images accurately. But for drawbacks of clustering and immature features, it can't locate background-like and skewed text.
对于区域分割，使用基于加权平方欧式距离的均值聚类算法代替传统的均值聚类算法。
It applies weighted K-means clustering for region segmentation, instead of traditional K-means clustering.
首先用阈值分割法去除红毛丹背景，然后用模糊C均值聚类方法来分割果肉区域。
The rambutan flesh was segmented using the FCM (fuzzy C-mean) clustering method after removing the background of the image.
通过聚类，人们能够识别密集的和稀疏的区域，因而发现全局的分布模式，以及数据属性之间有趣的相互关系。
By clustering, one can identity dense and sparse regions, therefore, discover overall distribution patterns and interesting correlations among data attributes.
最后利用所得的聚类中心值和FCM算法对未确定类别区域进行聚类。
The value of cluster centers and FCM are adopted to determine the undetermined cluster regions.
最后利用所得的聚类中心值和FCM算法对未确定类别区域进行聚类。
The value of cluster centers and FCM are adopted to determine the undetermined cluster regions.
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