最后利用自适应阈值实现红外目标分割。
Finally, infrared target is segmented by the adaptive threshold.
实验结果表明，水下目标分割方法是有效且可行的。
Experiments demonstrate that this method is efficient and feasible.
最后对预处理后的图像采用自适应门限进行目标分割。
At last, adaptive threshold is used to segment the targets in the image whose background is removed.
分割试验显示了该运动目标分割方法的有效性和可行性。
Segmentation experiments show the effectivity and feasibility of the segmentation method.
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。
An effective infrared object segmentation method based on recursive threshold analysis is proposed.
提出了一种建立在红外多波段图像基础上的目标分割新方法。
A new infrared target segmentation method based on infrared multiband images is proposed.
本文研究了融入SAR图像散射中心的统计信息于目标分割。
The statistical information of scattering centers in SAR DB images is proposed to add in segmentation.
运动目标识别跟踪系统中，目标分割是至关重要的处理环节。
Targets segmentation is a fundamental part in targets tracking and recognition systems.
提出了利用图像局部最大熵进行区域增长的多目标分割方法。
A method of region growth based on maximum value of local entropy is developed.
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。
Video object segmentation and stereo correspondence is a key technology in object-based stereo video coding.
实验表明，改进的方法有更高的精准度和对多目标分割的能力。
Experimental results show that the improved method is more accurate and capable of segmenting multi-targets.
满足了目标分割在工程上的速度快、准确度高、鲁棒性好等要求。
Therefore, this method can meet the needs of high speed, exactness and robustness in engineering field.
文中提出了利用SEM算法和区域生长法相结合的方法进行目标分割。
An algorithm, which combines SEM algorithm and region growing method, is put up to segment target.
最后，对得到的二值图像进行形态学变换，得到精确的目标分割区域。
Finally, the threshold image was filtered by morphological filter and then accurate target region was obtained.
提出了将高阶统计运动检测和多尺度分水岭相结合的视频目标分割算法。
An algorithm extracting video object is proposed by utilizing the HOS (higher order statistics) and multi-resolution watershed algorithm in video sequences.
针对上述问题，提出了一种用于智能交通系统的新的运动目标分割方法。
To cope with these problems, a novel segmentation method is proposed for intelligent transportation system.
提出了一种对复杂云层背景下红外图像序列中弱小运动目标分割和检测的方法。
An efficient approach for segmenting and detecting small moving target in infrared image sequences against complex cloud layer background is given.
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。
Objective Based on a computerized color object segmentation technology, a novel ultrasonogram color flow pels quantitative analysis method is proposed.
目标分割前，在每一次迭代分割过程中计算目标的尺寸、形状以及其灰度变化范围。
Before thresholding an object, in each iteration of the thresholding process, the algorithm calculates the size, shape and g...
红外图像点目标检测一般可分为三个阶段，依次为图像预处理、目标分割和目标检测。
In general, point target detection of Infrared image can be divided into three phases, followed by image preprocessing, target segmentation and target detection.
因此，有必要研究细胞神经网络在视频序列图像中目标分割和追踪的应用及其相关算法。
So, it is necessary to study the segment and the tracking of moving object in video image.
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。
For pathological information management system, which is based on content retrieving, technology of object segmentation is always an important part of parametric measurement.
实验结果表明，本文算法在部分遮挡、光线变化等情况下，能准确实现运动目标分割与跟踪。
Experiment results proved that this algorithm can accurately settle with the problem of objects segmentation and tracking problem under the case of partial shelter, and illumination change.
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。
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.
基于视频序列的数字图像拼接技术主要包括全局快速配准算法、运动目标分割算法和无缝融合算法。
The techniques of digital image mosaics from video sequence consist of image global fast registration algorithm, motion object segment algorithm, and seamless blending algorithm.
实验结果表明，使用该方法的目标分割正确率达97.3%，显示了较高的分割精度和较强的鲁棒性。
Experiment result shows that with this method, the accuracy of target segmentation can be up to 97.3% and the performance shows good robustness.
提出一种以目标检测、目标分割、目标方位角估计和目标不变性特征提取为线索的SAR目标识别框架。
We propose a multistage SAR target recognition process based on target detection, target segmentation, target aspect estimation and invariant feature extraction.
提出一种以目标检测、目标分割、目标方位角估计和目标不变性特征提取为线索的SAR目标识别框架。
We propose a multistage SAR target recognition process based on target detection, target segmentation, target aspect estimation and invariant feature extraction.
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