通过提取直方图的外层，以及计算像素点周围的局部模糊程度来更新粗糙度。
By extracting encrustation of histogram, and calculating partial fuzzy extent around pixels to update the fuzzy roughness.
针对目标模型内的背景像素造成目标跟踪定位偏差的问题，提出了一种适合于目标跟踪的模糊核直方图。
To resolve the problem that the background pixels in an object model induce localization errors in object tracking, a fuzzy kernel histogram was presented for object tracking.
针对最大熵阈值分割算法的计算缺陷，提出了一种基于直方图的模糊最大指数熵阈值图像分割新算法。
To overcome the defects of image segmentation by maximum entropy, a new method of image segmentation was presented by using fuzzy maximum exponential entropy based on histogram.
用户通过设置隶属函数的参数、直方图的值调整模糊范围的大小，通过设置不同的可信度查询不同可靠性的数据。
Users can adapt the scale of fuzzy range by setting parameter in membership function or altering values in the histogram, and set different confidence to query different reliable data.
该方法通过定义图像的平滑性测度，采用模糊增强技术对图像的灰度直方图进行增强，然后在增强的直方图上，利用自适应多阈值分割方法进行图像分割。
By defining a region smoothness measure, the method firstly enhances peak-valley feature of image histogram by fuzzy set technique, and then segments image using adaptive multi-thresholding method.
该文提出了一种通过最大化二维直方图模糊划分熵分割灰度图像的新算法。
In this paper a novel method is presented to segment gray level image through maximizing the fuzzy partition entropy of two-dimensional histogram.
主要研究成果归纳如下：首先，针对目标和背景严重重叠、直方图为单峰的图像，提出了适合该类图像的一种新的模糊熵。
The main research results can be concluded as follows:First, a new fuzzy entropy method is proposed for the image of target and background are seriously overlapped and the single histogram modal.
把二维直方图方法应用于模糊门限分割中，提出了一种基于二维直方图的模糊门限分割方法。
A new fuzzy thresholding method of image segmentation is presented which is based on the two-dimensional histogram.
并考虑在一维分割特征向量情况下，通过引入直方图统计特性，实现了模糊C-均值算法的快速运算。
Under considering 1- D segmentation character vector, the histogram is introduced, and the speed of F CM is greatly increased.
最后对具有多峰直方图分布图像的模糊增强方法进行了推广。
This algorithm is also extended to the enhancement of the multi-threshold image.
处理结果有效地去除原图像的斑点噪声，使图像中较模糊、对比度差的细节得到增强，优于传统的直方图均衡增强方法。
And the output image has adequate contrast, obvious levels. The dim and low-contrast detail has been enhanced. The method is preceded with that the histogram enhancement.
基于多特征联合分布直方图理论和模糊c -均值聚类算法，我们提出了新的视频流模糊检索方法。
We bring out our video retrieval method based on multi-feature data association histogram and C-Mean fuzzy clustering algorithm.
针对医学内窥镜图像，提出两种基于模糊C-均值聚类（FCM）的特征融合算法：融合颜色相关图和图像纹理特征算法以及融合颜色直方图和颜色相关图算法。
This paper presents two feature fusion algorithms of medical image retrieval about endoscopic image based on FCM as follow:first, using color correlogram combining with color texture;
针对医学内窥镜图像，提出两种基于模糊C-均值聚类（FCM）的特征融合算法：融合颜色相关图和图像纹理特征算法以及融合颜色直方图和颜色相关图算法。
This paper presents two feature fusion algorithms of medical image retrieval about endoscopic image based on FCM as follow:first, using color correlogram combining with color texture;
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