改进Split-Merge分割用于蝗虫图像

为了更好地分割蝗虫图像,对传统Split-Merge算法做出改进：用PCNN来进行分裂,采用一种简化的Mumford-Shah模型进行合并。该方法的优点是：分裂阶段不仅无效分割数目减少,而且无方块效应,对边缘定位准确;合并阶段能够理想地将分裂后的区域合并为感兴趣的前景与不感兴趣的背景,误合并与欠合并大幅减小。实验对成虫与幼虫图像均进行分割。综合比较,该算法性能较优。     

基于边缘检测与分裂合并的图像分割算法

针对传统分裂合并算法容易产生方块效应与过分割的缺点,提出了一种结合边缘检测和分裂合并的图像分割算法.该算法直接利用图像的边缘信息进行分裂,不断将图像分裂为一些不规则形状的一致性区域,然后根据一定规则将相似的区域合并.实验表明,该算法能大幅减少分裂次数,并有效克服方块效应和过分割等缺点,图像分割效果较好.     

基于Morton码的图像分裂合并算法研究

分裂合并算法是一种基于区域的串行图像分割算法.在图像的分裂阶段,从图像区域的表示出发,引入Morton码,降低了算法的空间复杂度.同时在图像的相邻区域的合并阶段,提出了一种新的合并原则,增加了满足合并条件的相邻区域的匹配率,减少算法的迭代次数,提高了算法的执行效率.最后给出并分析了相关的实验数据,证明了算法的有效性.     

基于K均值聚类与区域合并的彩色图像分割算法

提出一种基于K均值聚类与区域合并的彩色图像分割算法。首先,对图像运用mean shift算法进行滤波,在对图像进行平滑的同时保持图像的边缘;然后,运用K均值算法对图像在颜色空间进行聚类,得到初始分割的结果;最后,给出了一种区域合并策略,对初始分割获得的区域进行合并,得到最终的分割结果。仿真结果表明,算法的分割结果和人的主观视觉感知具有良好的一致性。     

基于改进分水岭变换的矿石图像分割算法

为了准确测量传送带上的矿石尺寸,提出了一种局部自适应阈值化和改进的分水岭变换相结合的矿石图像分割算法.该算法利用基于积分图像的自适应阈值化算法提取矿石区域;对二值图像做距离变换与双边滤波处理,并应用提出的基于区域合并的分水岭变换算法对图像进行分割;将提取的矿石区域与分割结果进行合并,得到最终的分割结果.对现场采集的复杂的矿石图像进行仿真实验,实验结果表明,该算法分割准确、速度快、光照自适应强.     

在Split—Merge框架下进行基于图的图像分割

Split-Merge算法是图像分割领域的经典算法,思路简洁、运算效率高,但因分裂位置和形状固定,导致出现方块效应和边界定位不准确等问题.现有的各种改进算法不能从根本上解决这些问题,为此本文将基于图的分割算法纳入到Split-Merge框架中来,提出了在Split-Merge框架下进行基于图的分割.新算法把传统的基于图割值的算法作为分裂阶段的处理手段,在合并阶段采用本文提出的一种与访问次序无关的合并算法.新算法既解决了Split-Merge算法中因分裂位置和形状固定而带来的各种问题,也有效地消除了在基于图的分割中常见的"过分割"现象,取得了满意的分割效果.     

改进的自适应模糊ISODATA灰度图像分割算法

传统模糊ISODATA（Fuzzy ISODATA,FISODATA）算法中,分裂-合并操作需人工选取阈值参数。而不适当的阈值往往使算法陷入局部极值,因而得到错误的类属数并最终影响图像分割结果。为此,在模糊集理论基础上提出一种改进的自适应FISODATA算法。该算法设计了自适应分裂-合并操作,即在每次分裂-合并后,根据该次计算结果改变参数阈值,解决了人为选取参数带来的诸多问题。利用该算法对模拟图像和真实IKONOS图像进行分割实验,均能得到良好的分割结果。     

基于二叉划分树的多尺度图像分割算法

图像分割作为从图像中提取感兴趣对象的必要步骤,通常需要其能够提供多尺度的分割结果.提出一种基于二叉划分树(BPT)的多尺度图像分割算法,用于系统地记录从图像的任意过分割结果上进行的区域合并过程;然后基于BPT中每个结点与其父亲结点的差异度量,提出一种包括自动确定候选结点和分裂合并策略的结点选择算法,来选出符合期望分割区域数目的结点,并生成相应尺度的分割结果.实验结果表明,文中算法能够在较粗分割尺度下获得更适合于对象提取的分割结果,有助于提高自动对象提取的效率以及减少交互式对象提取中的人工交互.     

基于分裂合并算法的道路标线分割方法研究

针对现有的道路标线分割方法在阴影、光照、裂缝等干扰下存在分割精度不足的问题,提出了基于分裂合并算法的道路标线分割方法.该方法通过分析道路标线图像的灰度、边缘、纹理特征,首先采用Bresenham算法进行道路标线有无判定,并根据道路标线边缘实现路面检测图像标线区域和非标线区域的分裂,然后采用基于重心连线灰度值的区域合并和基于灰度与直线边缘特征的区域合并两种方法进行道路标线区域合并,最终完成道路标线的准确分割.实验表明,该方法分割精度较高,具有良好的抗噪性能,能够很好地满足道路检测车采集图像实时处理的需求.     

基于改进的分水岭算法图像分割方法研究

研究图像分割中保真问题,针对目前分水岭算法易产生过分割现象,导致图像分割边缘不明显现象,使得分割以后图像失真较大.为了解决上述问题,提出了一种基于空间模式聚类算法和分水岭算法相结合的图像分割方法.首先对图像采用分水岭算法进行图像分割,然后对产生过分割现象的图像区域采用基于空间模式聚类方案进行合并.仿真结果表明,与传统的分水岭图像分割方法相比,分割出的图像边缘效果明显清晰,有效保证原图效果.     

基于层次与划分方法的聚类算法研究

针对在层次聚类算法中,一个分裂或合并被执行,就不能修正,其聚类质量受到限制的缺陷,提出了利用簇间相异度及基于信息熵或整体相似度的聚类质量评价标准,在簇分裂过程中动态的进行簇的合并与分裂的算法。仿真实验结果证明,该算法具有使结果簇更紧凑和独立的效果,具有更好的聚类质量。     

Evolving Takagi–Sugeno fuzzy model based on switching to neighboring models

In this paper, we propose a new online identification approach for evolving Takagi–Sugeno (TS) fuzzy models. Here, for a TS model, a certain number of models as neighboring models are defined and then the TS model switches to one of them at each stage of evolving. We define neighboring models for an in-progress (current) TS model as its fairly evolved versions, which are different with it just in two fuzzy rules. To generate neighboring models for the current model, we apply specially designed split and merge operations. By each split operation, a fuzzy rule is replaced with two rules; while by each merge operation, two fuzzy rules combine to one rule. Among neighboring models, the one with the minimum sum of squared errors – on certain time intervals – replaces the current model.To reduce the computational load of the proposed evolving TS model, straightforward relations between outputs of neighboring models and that of current model are established. Also, to reduce the number of rules, we define and use first-order TS fuzzy models whose generated local linear models can be localized in flexible fuzzy subspaces. To demonstrate the improved performance of the proposed identification approach, the efficiency of the evolving TS model is studied in prediction of monthly sunspot number and forecast of daily electrical power consumption. The prediction and modeling results are compared with that of some important existing evolving fuzzy systems.     

Unsafe operations in B-trees

Summary A simple mathematical model for analyzing the dynamics of a B-tree node is presented. From the solution of the model, it is shown that the simple technique of allowing a B-tree node to be slightly less than half full can significantly reduce the rate of split, merge and borrow operations. We call split, merge, borrow and balance operations unsafe operations in this paper. In a multi-user environment, a lower unsafe operation rate implies less blocking and higher throughput, even when tailored concurrency control algorithms (e.g., that proposed by Lehman and Yao [10]) are used. A lower unsafe operation rate also means a longer life time of an optimally initialized B-tree (e.g., compact B-tree). It is in general useful to have an analytical model which can predict the rate of unsafe operations in a dynamic data structure, not only for comparing the behavior of variations of B-trees, but also for characterizing workload for performance evaluation of different concurrency control algorithms for such data structures. The model presented in this paper represents a starting point in this direction.     

Adaptive cloud simulation using position based fluids

In this paper, we propose a method for the simulation of clouds using particles exclusively. The method is based on position based fluids, which simulates fluids using position constraints. To reduce the simulation time, we have used adaptive splitting and merging to concentrate computation on regions where it is most needed. When clouds are formed, particles are split so as to add more details to the generated cloud surface and when they disappear, particles are merged back. We implement our adaptive method on the Graphics Processing Unit (GPU) to accelerate the computation. While the splitting portion is easily parallelizable, the merge portion is not. We develop a simple algorithm to address this problem and achieve reasonable simulation times. Copyright © 2015 John Wiley & Sons, Ltd.     

基于三角形二叉树的实时大规模地形渲染算法

提出一种大规模地形渲染算法,对大规模地形进行分块,用三角形二叉树表示地形网格,在实时漫游中,通过强制分割和强制合并实时更新网格,充分利用帧与帧之间的连贯性并自动避免裂缝。实验结果表明,该算法可以有效提高ROAM算法性能,能以较高帧速实现大规模地形的实时漫游。     

Clustering over Multiple Evolving Streams by Events and Correlations

In applications of multiple data streams such as stock market trading and sensor network data analysis, the clusters of streams change at different times because of data evolution. The information about evolving cluster is valuable to support corresponding online decisions. In this paper, we present a framework for clustering over multiple evolving streams by correlations and events, which, abbreviated as COMET-CORE, monitors the distribution of clusters over multiple data streams based on their correlation. Instead of directly clustering the multiple data streams periodically, COMET-CORE applies efficient cluster split and merge processes only when significant cluster evolution happens. Accordingly, we devise an event detection mechanism to signal the cluster adjustments. The coming streams are smoothed as sequences of end points by employing piecewise linear approximation. At the time when end points are generated, weighted correlations between streams are updated. End points are good indicators of significant change in streams, and this is a main cause of a cluster evolution event. When an event occurs, through split and merge operations we can report the latest clustering results. As shown in our experimental studies, COMET-CORE can be performed effectively with good clustering quality.     

EM algorithms for Gaussian mixtures with split-and-merge operation

In order to alleviate the problem of local convergence of the usual EM algorithm, a split-and-merge operation is introduced into the EM algorithm for Gaussian mixtures. The split-and-merge equations are first presented theoretically. These equations show that the merge operation is a well-posed problem, whereas the split operation is an ill-posed problem because it is the inverse procedure of the merge. Two methods for solving this ill-posed problem are developed through the singular value decomposition and the Cholesky decomposition. Accordingly, a new modified EM algorithm is constructed. Our experiments demonstrate that this algorithm is efficient for unsupervised color image segmentation.     

Thermal structure of an agricultural region as seen by NOAA-7 AVHRR

Using a split and merge image segmentation algorithm on NOAA-7 AVHRR channel four data, the thermal structure of an agricultural homogeneous region (the Beauce Plateau in France) around midday is studied during 1982. It is shown that the image homogeneous areas can be identified with known natural regions: hills, forest, and the Beauce Plateau. The Beauce Plateau has a thermal structure divided into three or more areas depending on the season. Those areas are very well correlated with regions of equal soil water availability.