Three feature sets were adopted, including 20 global features, 10 statistical histogram features and 3 color features.
即20个综合性特征、10个统计性直方图特征和3个颜色特征。
The features concerned are such as texture feature, gray histogram feature and features derive form the principle component analysis.
在图像特征提取上改进并提出了三种特征的提取：纹理特征，灰度直方图均值化特征，图像的主成分特征。
In this article, we proposed and implemented a human tracking system whose bottom layer is human detectors based HOG feature and color histogram feature, and upper layer is based on particle filter.
本文提出并实现了一套完整的行人跟踪系统，整个系统的底层是由HOG特征和颜色直方图特征构成的行人检测器，上层则采用粒子滤波器算法，结合各个行人检测器的结果得到最终检测结果。
Feature extraction based on the histogram, texture, projection and shape of the defect images was also investigated.
研究了基于缺陷图像直方图、纹理、投影和形状的特征提取。
A novel gradient orientation histogram was built using a Gaussian-weighted circular window and a major orientation to each feature point was assigned based on local image properties.
构建了一种新的局部梯度方向直方图，同时定义了特征点的主方向，从而提出了一种具有旋转不变性的图像配准算法。
Finally, the wavelet packet histogram is computed as feature signatures and histogram intersection distance is employed to retrieval queried image from image databases.
最后，抽取小波包直方图作为特征表示并应用直方图相交距离从图像数据库中检索被查询图像。
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。
Introduces color feature extraction and matching algorithms in content-based image retrieval, such as weighted Euclidean-distance, weighted centre distance, histogram intersection algorithm, etc.
介绍了基于内容图像检索中多种颜色的特征提取和匹配算法，以及加权欧几里得距离、中心距的加权距离、直方图交集算法等。
Results Parameters including mean value and skewness gotten from histogram can reflected the all texture feature of images of fatty and normal liver.
结果从直方图分析中提取的均值、斜态均能反映两类图像所特有的纹理特征。
To represent color feature, local color cumulative histogram is computed, we also extract the color moments of partitions to solve the problem of lacking the spatial knowledge.
对于颜色特征，计算图像颜色的局部累加直方图，同时提取分块的颜色矩弥补其不包含颜色空间分布关系的缺点。
To solve the first problem, a spatially weighted LBP histogram is proposed to be the feature vector and a shadow removing method is introduced.
为了解决第一个问题，本文提出用空间加权的LBP直方图作为特征并引入了阴影消除算法。
Another less robust but potentially faster solution is to build feature histograms for each image, and choose the image with the histogram closest to the input image's histogram.
另一个不太可靠的，但可能更快解决方案是构建特征直方图的每个图像，并且选择图像与最接近直方图于输入图像的直方图。
Local gray histogram statistics is applied to object detection in the images with multi-scale fractal feature.
在多尺度分形新特征图像中采用局部直方图统计方法进行目标检测。
The existing color feature extraction methods include color histogram, accumulative color histogram, color moments.
传统的颜色特征提取方法主要包括颜色直方图、累积直方图、颜色矩等。
Feature space imitates the model of biological complex neurons in primary visual cortex, and it is constructed through orientation histogram in feature's local area.
特征空间则模仿了灵长类动物的视觉神经元模型，以区域图像梯度直方图的方式建立。
Finally, the similarity between color images is computed by using a combined feature index based on the color histogram and texture histogram for local grids.
最后综合利用上述网格区域的颜色直方图和纹理直方图来计算图像间内容的相似度，用于进行彩色图像检索。
Then the features of color histogram and MPEG-7 edge histogram of each key frame are computed and the feature vectors of shot key frames are formed.
然后计算关键帧的颜色直方图和MPEG-7边缘直方图，以形成关键帧的特征；
Based on the quantization of the color in HSV model, color histogram is introduced as the color feature.
在对HSV颜色模型量化处理的基础上，提取颜色直方图作为图像的颜色特征。
We bring out our video retrieval method based on multi-feature data association histogram and C-Mean fuzzy clustering algorithm.
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.
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。
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