因此，对图像对象分割理论及其相关技术进行研究具有十分重要的意义。
Therefore, the study on the theories and related technologies of image object segmentation is quite meaningful.
视频对象分割是当前图像和视频处理的热点和难点之一。
Video object segmentation is the one of the focus in the field of image and video processing.
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.
本论文以短跑为研究对象，以计算机为工具，首先采用先分割再填充的方法，获得不重影、不抖动的图像。
The thesis takes dash as object of study, takes computer as implement, first, uses the method which divides first fills again, obtains image which the double image, does not vibrate.
提出一种基于原型的可变形模板进行图像分割的算法，从而可以将感兴趣的视频对象从静止的复杂背景中提取出来。
This paper proposes an image segmentation algorithm using deformable template to segment an interesting visual object from the stationary complex background.
本文以遥感图像为主要的分割对象，对图像分割的相关技术进行了研究，并提出了一种有效的遥感图像分割方法。
This paper used RS images as the primary segmentation object, made a study of RS image segmentation methods, and proposed an effective method for RS image segmentation.
该方法无需对图像进行复杂的分割就能提取对象特征，且经由实验证明具有较高的查全率。
This approach can extract the feature of object without segmentation, and our experiments show that it can achieve high rate of recall.
视频运动对象的自动分割是实现新一代对象基视频编码标准MPEG - 4的重要技术，本文提出了一种基于帧内图像分区的运动对象自动分割算法。
Automatic segmentation of moving objects in video sequences is a significant technology for implementing emerging object-based video coding standard MPEG-4.
通过灰度拉伸增强图像对比度，通过二值化处理实现图像中背景和对象的分割。
The contrast of the image was enhanced by gray expanding and the key threshold of the binarization algorithm was determined based on the dynamical threshold method.
将视频图像的方向信息测度、颜色和运动信息相结合的视频对象分割算法可以解决这一问题。
A new approach to extract video objects from video sequence by combining of orientation information measure, color and motion information is presented.
针对基于对象的视频编码应用，提出了一种基于运动的区域生长分割方案，将图像分割成具有一致运动特征的区域。
This paper proposes a motion based region growing segmentation scheme for the object based video coding which segments an image into homogeneous regions characterized by a coherent motion.
针对视频图像中单个运动对象的分割和跟踪问题，提出了一种基于时空离散度的视频对象分割跟踪算法。
To solve the problem in segmentation and tracking the moving object in video sequence, a novel moving object segmentation and tracking approach is proposed based on spatial-temporal dispersions.
本文处理的对象是灰度图像，分割的核心是对像素进行聚类，属于优化问题。
This thesis deals with gray image. The kernel of segmentation is pixel clustering. It belongs to optimization problem.
首先计算整幅图像的模糊连接度，通过阈值分割提取出感兴趣的对象，并将模糊连接度作为图像的冗余特征；
First, the object with interest is extracted and a new image scene is constructed using fuzzy connectedness-based method.
为了实现较完整的视频对象分割，提出了一种基于视频图像边缘信息和最小错误率的贝叶斯决策理论的视频对象分割算法。
To realize video object segment, we proposed one algorithm base on Bayes decision-making theory with least risk and video sequence edge information.
可见图像分割、对象特征提取、基于特征设计识别算法，是图像对象识别的关键问题。
Firstly segment the object from images, then extract the features of the object, and finally identify the object based on the features.
解决这个问题的办法是采用色彩分割，它既考虑图像对图像的匹配，又考虑对象定位。
A solution to address this problem is to apply color segmentation, which allows both image-to-image matching and object localization.
针对对象选择了代表目标的模型的情况下，方法1跟随至图像分割步骤19，其中，执行了合适的分割。
In case when for the object a model representative of the target is selected, the method 1 follows to the image segmentation step 19, whereby a suitable segmentation is performed.
但对图像进行分割在一般意义下十分因难，目前的图像分割算法都是针对分割对象的技术，与具体问题相关。
Generally speaking, to segment an image is very difficult. The current image segmentation algorithm is the technology aiming at the object of segmentation and it is also related to the certain issues.
但对图像进行分割在一般意义下十分因难，目前的图像分割算法都是针对分割对象的技术，与具体问题相关。
Generally speaking, to segment an image is very difficult. The current image segmentation algorithm is the technology aiming at the object of segmentation and it is also related to the certain issues.
应用推荐