提出一种基于对象语义的图像分割和分类方法。
This paper proposes a novel approach to object semanteme based image segmentation and classification.
手写汉字分割和多类别金融票据图像分类是实现票据自动处理的基础。
The segmentation of handwritten Chinese words and the classification of multi-sort financial notes images is the basis of implementation of notes automatic procession.
本文主要研究文本页面图像的分割与分类算法。
The main purpose of this thesis is to study algorithms for page segmentation and classification of document images.
对特征进行分类，完成图像的分割。
The fractal dimensions are classified and the image segmentation is completed.
针对SAR图像解译，SVM在图像滤波、图像分割、目标识别与分类、极化数据分类等过程中有很好的处理能力。
Aimed at SAR image interpretation, SVM shows good performance in image filtering, image segmentation, target discrimination and classification, as well as polarimetric SAR data classification.
本文采用的技术包括：皮肤检测、人脸检测、目标区域分割、敏感图像特征提取、分类器设计及过滤器在浏览器上的实现等。
Some key techniques are included, such as skin detection, face detection, object area segmentation, image features extraction, the design of classifier and the implement of filter based on browser.
肤色检测、皮肤的纹理分析检测、目标区域的分割、图像特征的提取、分类器的设计。
The key technique include skin color detection, skin texture analysis, object area segmentation, image features extraction and the design of classifier.
储粮害虫图像有效分割是粮虫特征提取和识别分类的基础和依据。
Stored grain insect image segmentation always laid the basis for insects feature extraction and recognition and classification.
本文提出了一种结合贝叶斯分类的水平集方法用于医学图像分割。
In this paper, a level set segmentation algorithm based on Bayesian classification for medical image segmentation was proposed.
海天背景下目标图像的分割，即把目标从海天背景中提取出来，以便于对目标进行自动地探测、跟踪、分类和识别。
The image segmentation on the background of sea and sky is that extract the target from the background, to search, track, class and identify.
作为一种重要的分类器，模糊聚类技术在磁共振图像的分割中已经得到了成功的应用，并成为了一种有效的磁共振图像的分割工具。
As an important classifier, fuzzy clustering technique has been widely used in segmentation of MRI image and became an effective segmentation tool of MR image.
在一个“好”的分类标准的控制下，实现对图像的分割。
A criterion for "good" segmentation using this class-map used to segment the image.
设计了基于颜色的皮肤分类器对图像中的皮肤区域和非皮肤区域进行分割；
Designed a color-based skin classifier to segment human skin regions from non-skin regions.
本文主要利用粗集理论针对图像分割后的区域形状进行分类研究。
The classification research of regional shape after image segmentation is brought forward in this paper based on RS theory.
利用窗口分割技术对缝线图像进行图像分割处理，通过BP神经网络作为分类器进行类型识别。
It brought forward a method with a window segmentation technology to segment the seam images. The BP neural network was designed to conduct the classification work.
图像分割是进行正确分类和识别的基础，是图像处理领域中的关键问题。
The segmentation is the key procedures and the basis of segmentation and recognition in digital image field.
为了能对包含不规则图片区和表格的倾斜文本页面图像进行图文分割与分类，提出了一种新的图文分割和分类算法。
In this paper, a system valid of the segmentation and classification of skewed document images with irregular graph regions and form regions is proposed.
然后利用图像分析技术，采用基于边缘的图像分割方法，提取图像的主体区域并进行视觉特征提取与（分类）识别。
Then we use the technology of image analysis and image division based on the edge to extract the main object and to recognize (classify) the visual characteristic.
因此有必要对文档图像进行分割和分类，在文字区域和图像区域分别添加水印。
Thus, it's necessary to separate the document image and then embed watermarking in character area and image area.
最后根据SAR图像的统计性质，利用基于混合模型估计的分类后验概率将初始分割结果逐尺度进行细化得到SAR图像的最终分割。
Third, the initial segmentation is refined scale by scale to get the final segmentation of the SAR image based on the posterior probability of classification which is estimated by the mixture model.
帘子布疵点自动检测分为三个部分来完成，分别是图像的预处理、图像分割以及疵点的识别分类。
It is included three parts, namely, image preprocessing, image segmentation and identification classification of the defects.
对分割后的图像，本文采用黑白像素比（BWR）及黑白像素交替变换数（CC）两个特征进行进一步的分类。
To classify different segmented regions as text regions or non-text regions, two features of the black to white pixel ratio (BWR) and the cross-count (CC) of pixels were used for the classifications.
要实现对缺陷的分类识别，首先要进行缺陷图像的分割，以得到图像中的缺陷目标。
To realize the identification of defects, the first step is to segment defect images to get defects targets.
提出一种先对训练样本进行筛选，再进行分类（分割）的支持向量图像分割方法；
The first level SVM filters out the mistaking samples, and the second level SVM segments the images.
提出一种先对训练样本进行筛选，再进行分类（分割）的支持向量图像分割方法；
The first level SVM filters out the mistaking samples, and the second level SVM segments the images.
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