Video object segmentation and stereo correspondence is a key technology in object-based stereo video coding.
视频目标分割与立体匹配是目标基立体视频编码中的核心技术。
This paper introduces video segmentation of temporal segmentation and spatial segmentation, presents a video object segmentation algorithm based on multi-frames difference.
文章介绍了基于内容的时域及空域视频分割技术，提出了一种基于多帧差异的视频对象分割算法。
Video object segmentation has important application in content-based video encoding and video retrieval.
视频对象分割在基于内容的视频编码和视频检索中均有重要的应用。
Objective Based on a computerized color object segmentation technology, a novel ultrasonogram color flow pels quantitative analysis method is proposed.
目的提出一种新的基于计算机彩色目标分割技术的声像图彩色血流像素定量技术。
Video object segmentation is an important task in object based video coding.
在基于对象的视频编码中，视频对象的分割是重要的任务。
This paper proposes a novel approach to object semanteme based image segmentation and classification.
提出一种基于对象语义的图像分割和分类方法。
Video object segmentation techniques are also important tools for content-based video coding and manipulation, and interactive multimedia application.
视频对象分割技术同时也是基于内容的视频编码、视频内容操作和交互式多媒体等应用的重要工具。
Proposes an algorithm to determine the true motion vectors of the feature regions for object based video coding and segmentation applications.
针对物体基视频编码与分割应用，提出了求取特征区域真实运动矢量的一种算法。
Video object segmentation techniques are also important tools for content-based video coding and manipulation, and interactive multimedia applications.
视频对象分割技术同时也是基于内容的视频编码、视频内容的操纵和交互式多媒体等应用的重要工具。
Based on the practice of mobile robot vision navigation, the paper presents methods of image segmentation based on color models and object recognition.
基于移动机器人视觉处理的实践，提出了基于颜色模型的图像分割方法。
For pathological information management system, which is based on content retrieving, technology of object segmentation is always an important part of parametric measurement.
基于内容检索的病理信息管理系统中，目标分割技术始终是特征参数测量的一个重要环节。
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 and implements a moving object segmentation method, which based on inter-frame difference.
为此，文章提出并实现了一种基于互帧差的视频运动对象分割方法。
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.
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。
In this paper, one kind of segmentation methods of manmade object based on edge detection is introduced, which applies fractal, morphology and others comprehensively.
介绍了一种综合运用分形、形态学等方法，基于边沿的自然场景中人造目标的分割方法。
An effective infrared object segmentation method based on recursive threshold analysis is proposed.
提出了一种有效的基于递归门限分析的红外目标分割方法。
The test results show that the object segmentation method based on recursive threshold analysis is effective. Its segmentation performance is better than the traditional methods.
试验结果证明，基于递归门限分析的方法是一种行之有效的目标分割方法，分割性能优于传统方法。
This paper presents a quick object image segmentation algorithm based on adaptive threshold against infrared object images in complex background.
针对复杂场景中的红外目标图象，本文提出了一种基于自适应阈值面的目标图象快速分割算法。
For the first step, a morphology operator-based video motion object segmentation algorithm is proposed.
为此提出了一种基于形态学算子的视频运动对象自动分割算法。
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.
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。
The segmentation of video is the basis of the video object extraction, processing and recognition. It is also the premise of the content-based video compression and retrieving.
视频序列分割是实现视频对象提取、处理和识别的基础，也是基于内容的视频压缩和检索的前提。
Structure grammar based on local area of collection of line segmentation and geometric element and number of classes of geometric element could extract manmade object from natural background.
基于直线段集合图像给定区域内直线线段的结构文法及其所含几何基元数目和几何基元种类将人造目标从自然背景中提取出来。
Automatic segmentation of moving objects in video sequences is a significant technology for implementing emerging object-based video coding standard MPEG-4.
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。
An object region segmentation approach based on morphological method is proposed.
提出了一种基于形态学的目标图像区域划分方法。
Object-based video coding mostly includes video object segmentation and video object coding.
基于对象的视频编码主要包括视频对象的分割和视频对象的编码两部分。
And a set of features combining color, shape and topological are extracted from each object. Based on the features, a classification criterion is employed to perform the map segmentation.
通过提取对象的颜色、形状和近邻关系等特征，建立分类标准，实现地形图的自动分层。
In the third step, a whole object was detected by a novel fusion method based on segmentation map and edge map.
在第三步骤中，将整个对象检测到一种新的融合方法，基于分割图和边缘图。
Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps.
首先在画素级上提取影像的纹理和形状结构特征，在构建的多尺度分割集影像上提取物件的区域光谱特征。
The new video coding standard MPEG-4 is enabling content-based function. It needs for the segmentation of semantically meaningful moving object in video sequences.
随着新的视频压缩标准MPEG - 4的出现，如何从视频序列中分割出在语义上有意义的单独运动对象显得极其重要。
The new video coding standard MPEG-4 is enabling content-based function. It needs for the segmentation of semantically meaningful moving object in video sequences.
随着新的视频压缩标准MPEG - 4的出现，如何从视频序列中分割出在语义上有意义的单独运动对象显得极其重要。
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