用阈值分割方法对图像信息特征进行提取。
Image character information is dug up with dividing up threshold value.
提出基于万有信息定律的图像阈值分割方法。
This paper proposes a new image thresholding segmentation method based on universal information law.
采用边缘检测和阈值分割方法进行软着陆安全区域选取。
Edge detection and threshold segment are used in safe landing area choice.
提出一种融合视觉感知和等周理论的图像阈值分割方法。
In this paper, a novel thresholding method based on human visual perception and isoperimetric theory is presented.
实验结果表明，本文提出的关联熵系数阈值分割方法是可行的。
Experimental results show that the thresholding method based on relative entropy coefficient in this paper is feasible.
第一种图像分割方法是基于局部分块的图像自适应阈值分割方法。
The first method is adaptive threshold segmentation based on local blocks of image.
对焊缝图像的二值化进行了研究，并提出了一种自适应的阈值分割方法；
The binarization of seam image are studied and an adaptive threshold adjusting method are worked out.
结合梯度和灰度这两种图像的本质特征，提出一种基于边界梯度控制的最大熵阈值分割方法。
Combining the two essential characteristics of the image, the gradient and the gray level, a threshold segmentation approach using maximum entropy with the gradient boundary control was proposed.
本文对现有的各种图像阈值分割方法进行综述，重点介绍了基于图像灰度直方图的阈值分割方法。
The threshold methods of image segmentation are surveyed in this article, especially those based on the gray level histogram.
脸部位置的检测定位主要建立肤色模型以及计算肤色相似度图，通过阈值分割方法进行分类和定位。
The method of face detection is establishment of skin color model and computation of similarity graph, then classify by threshold segmentation.
常用的阈值分割方法在对红外图像进行分割时，由于红外图像本身的特点，会出现准确性不高的问题。
In view of the characteristics of infrared image, the veracity is not good when the commonly used threshold is used in infrared image segmentation.
采用矩持阈值分割方法提取目标，采用质心跟踪算法及基于线性微分拟合的记忆外推跟踪技术跟踪目标。
The moment-preserving thresholding method is used to pick-up targets, the mass centroid tracking algorithm and linear-fitting predicting approach are used to tracking targets.
针对金相图中分割问题，在分析对比传统的全局阈值分割方法的基础上，提出了一种自适应阈值分割方法。
By analyzing the traditional thresholding methods (such as Otsu and Kapur), a new approach using the adaptive thresholding method is presented.
本文中可变阈值分割方法和“栅格”技术的采用，使该计算机视觉系统节省了时间，提高了精度和识别处理的速度。
In this paper changing threshold segmentation and grid technology is applied so that computer vision system is to save time, to improve accuracy and processing speed.
在工业无损检测等一系列图像上的实验结果表明，与现有的几种经典阈值分割方法相比，本文方法的分割效果更好。
Experimental results on a series of images including nondestructive testing ones show that authors' method outperforms several existing classic thresholding methods in segmentation quality.
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。
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.
使用限制候选区域和两次阈值分割的方法减少计算量，提高了计算精度。
And the method of limited candidate region and twice thresholds was used to reduce computation load and improve precision.
在体数据分割中我们分别讨论了基于阈值和基于区域的分割方法。
In volume data segmentation, the threshold based and region based methods are separately discussed.
最后采用混沌优化法来获得多阈值模糊互信息分割方法的最佳阈值。
Finally, the optimal thresholds of image segmentation based on fuzzy mutual information is obtained by means of chaos optimization method.
提出了多阈值模糊互信息图像分割新方法。
The new image multi-threshold method based on fuzzy mutual information is proposed.
提出了一种基于多重色彩转换和模糊阈值分割的垩白米检测方法。
This paper presents a chalky rice detection method that is studied based on multi-color conversion and fuzzy threshold segmentation.
基于模糊划分熵的图像阈值化分割方法因具有良好的分割性能已成为图像分割广泛应用的方法之一。
Image thresholding segmentation method based on fuzzy partition entropy has good segmentation performance and becomes a kind of extensive application method in image segmentation field.
该方法将图像平滑、区域分割、阈值分割等多种图像处理技术有机的结合，对采集的图片成功的实现目标汽车提取，并且具有计算速度快、准确性高的特点。
It combined the technology of image smooth, region segmentation and threshold segmentation and picked up the object auto. It has high speed and high veracity in program.
首先讨论了图像阈值分割的两种方法：全局阈值图像分割和动态阈值图像分割。
The paper firstly discussed two ways for image segmentation:image segmentation by global threshold and image segmentation by dynamic threshold.
应用实例结果表明，该方法能够快速有效地实现复杂图象的多阈值分割。
Experimental results show that this method can be effectively applied for the multi-threshold segmentation of complex images.
对焊接有缺陷的情况，利用基于AI的自动阈值选择方法，分割出缺陷区域，并对缺陷做定量分析。
Quantitative analysis of flaws is realized by using the method of selecting threshold automatically based on AI to segment the flows for the soldering flows condition.
用两种不同的图像分割方法(直方图阈值法和匹配法)实现图像分割，并且对两种方法的优缺点做了比较。
We use two different image segmentation methods, histogram algorithm and match algorithm, to implement image segmentation and compare the advantage and disadvantage of two methods.
用两种不同的图像分割方法(直方图阈值法和匹配法)实现图像分割，并且对两种方法的优缺点做了比较。
We use two different image segmentation methods, histogram algorithm and match algorithm, to implement image segmentation and compare the advantage and disadvantage of two methods.
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