可分割
- 与 可分割 相关的网络例句 [注:此内容来源于网络,仅供参考]
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I saw a utility yesterday that lets you access your Mac partition from a Vista Boot Camp partition.
我看到公用事业昨天表示,可让您存取您的Mac分区从Vista的新兵训练营分割。
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Using interlayer lily bud scale treated with 0.1% HgCl2 could increase cutting propagation rate significantly.
结论]百合鳞片扦插以不分割为好,采用百合中层鳞片,并用0.1% HgCl2处理,可显著提高扦插繁殖率。
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It's difficult to apply the methods which process static fluorescent images to our experiment. We propose a self-adaptive segmentation based on spatial point pattern cluster features comparability in Markov field.
该文就心肌细胞Ca2+离子定量研究过程中遇到的这一问题,提出一种基于马尔可夫场和空间点模式的特征聚类相似性测度的自适应图像分割算法。
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In new algorithm, it is not necessary to calculate grey-level threshold for each X-ray image which is inevitable in Bentz el als method. So the new algorithm is more general, computational and error tolerance.
经对比发现,新算法能达到与Bentz等人的算法相同的分割精度,可以扩充,并且不需要确定各X-射线图像的灰度阈值,具有更强的通用性、可计算性和容错性。
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But the ODOG based on the vision selective attention mechanism can effectively collect the interesting information and then segment the image by the coupled oscillation of the PCNN.
而基于视觉选择注意机制的方向性高斯差算子通过模拟生物视觉感受野的特点,在有效提取感兴趣区域的信息后,再通过脉冲耦合神经网络模型的自适应振荡,可达到图像分割的目的。
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Deformable models ,also known as "snakes", have been one of the most active and successful research areas in image segmentation.
近年来,可变形模型鉴于其良好的性能,在医学图像分割中得到了广泛的应用。
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A novel method of content-based image segmentation using deformable template matching is proposed.
本文提出一种采用可变形模板匹配技术进行基于内容的图像分割算法。
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Dual tree complex wavelet transform ; Texture image segmentation ; Markov random field ; Bayesian estimation
对偶树复小波变换;纹理图像分割;马尔可夫随机场;贝叶斯估计
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It solves the problem that the unitary contour presentation can not correctly extract face contour in a face image which suffers from scale, rotation etc. The definition of the internal and external energy function is provided. At the same time, the global matching algorithm and local matching algorithm is given. The experiment shows that this presentation and the accompanying matching algorithm can be used to extract the face contour very well. So the image segmentation can be implemented by using it.②By analyzing the recognition principle of PCA method, we can conclude that the face images coming from different surrounding consist of different face image space. This is the essential reason that makes the generality of PCA method worse. Also, we give a measurement means to measure the distance from different face image space, so we can analyze face image space more conveniently.③We also construct various scale models and rotation pose models to detect the scale and rotating angle of face image to be recognized. The experiment results show that the detecting precision is very high. So it is good for face image feature extraction and face image representation.④Similarly, we construct local feature models of face image and utilize them to detect the local feature of face image. At the same time, we put forward a novel face image local feature detection algorithm, locating step by step. The experiment results show that this method can accurately detect the location of local face feature in a image.⑤A novel face image presentation model, dual attribute graph , is put forward. Firstly, it utilizes attribute graph to present the face image, then exact the local principal component coefficient and Gabor transform coefficient of thc pixels which corresponds to the nodes of the graph as the attribute of the nodes. This representation fully makes use of the statistical characteristic of the local face feature and utilizes Gabor transform to present the topographical structure of face image. So DAG has more general property.⑥Based on the DAG presentation, we give a DAG matching function and matching algorithm. During the design of the function and algorithm, the noise factor, e. g., lighting, scale and rotation pose are considered and tried to be eliminated. So the algorithm can give more general property.⑦A general face image recognition system is implemented. The experiment show the system can get better recognition performance under the noise surrounding of lighting, scale and rotation pose.
本文在上述研究的基础上,取得了如下主要研究成果:①构造了一个通用的人脸轮廓模型表示,解决了由于人脸图象尺度、旋转等因素而使得仅用单一轮廓表示无法正确提取人脸轮廓的问题,并给出了模型内、外能函数的定义,同时给出了模型的全局与局部匹配算法,实验表明,使用这种表示形式以及匹配算法,能够较好地提取人脸图象的轮廓,可实际用于人脸图象的分割;②深入分析了PCA方法的识别机制,得出不同成象条件下的人脸图象构成不同的人脸图象空间的结论,同时指出这也是造成PCA方法通用性较差的本质原因,并给出了不同人脸空间距离的一种度量方法,使用该度量方法能够直观地对人脸图象空间进行分析;③构造了各种尺度模板、旋转姿势模板以用于探测待识人脸图象的尺度、旋转角度,实验结果表明,探测精确度很高,从而有利于人脸图象特征提取,以及图象的有效表示;④构造了人脸图象的各局部特征模板,用于人脸图象局部特征的探测;同时提出了一种新的人脸图象局部特征探测法---逐步求精定位法,实验结果表明,使用这种方法能够精确地得到人脸图象各局部特征的位置;⑤提出了一种新的人脸图象表示法---双属性图表示法;利用属性图来表示人脸图象,并提取图节点对应图象位置的局部主成分特征系数以及Gabor变换系数作为图节点的属性,这种表示方法充分利用了人脸图象的局部特征的统计特性,并且使用Gabor变换来反映人脸图象的拓扑结构,从而使得双属性图表示法具有较强的通用性;⑥在双属性图表示的基础上,给出双属性图匹配函数及匹配算法,在函数及算法设计过程中,考虑并解决了光照、尺度、旋转姿势变化等因素对人脸图象识别的影响,使得匹配算法具有较强的通用性;⑦设计并实现了一个通用的人脸图象识别系统,实验结果表明,该系统在图象光照、尺度、旋转姿势情况下,得到了较好的识别效果。
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First scanning the known handwriting materials then number them ,In pretreatment, we convert the valid part of the image into a standard size, as images carries out duotone and go throw off chirp handling in order to achieve better effect.draw features from the known handwriting materials with the Co-occurence,especially,we divided a copy of handwriting into 25 little pieces with the size of 128*128 ,drawing features from every little piecese with four directions(0 degree, 45 degrees, 90 degrees as well as 135 degrees) and calculate the four major feature values( veins and the statistical quantity of veins contrast and the statistical quantity of veins consistency Shang the statistical quantity of statistical quantity as well as the veins correlation of gray scale ), preservation all the feature value that drawn from all known ma terials to the handwriting characteristic database,then input the unknown handwriting materials, also using the method of the Co-occurence to draw those features, recycling the minimum European Distance law match the unknown writing material feature value with the handwriting characteristic feature database, export the label of the known hand writing materials which is most similar to the unknown material with minimum European Distance, and then we can confirm who is the author of the unknown material.
首先将笔迹材料作为图象扫描输入,并对其进行编号。预处理部分可将笔迹图象的有效部分规范化到一个统一尺寸,接着对其进行二值化和去除噪声的处理,以便于更好的提取图像的特征。在此我们采用了灰度共生矩阵法提取手写笔迹材料的纹理特征,与以往有所不同的是,我们将一份手写材料分割成64块大小为80*80象素的子图象,每个小块都从四个方向(0度、45度、90度以及135度)来更全面的提取特征,并计算出四个最主要的特征值(纹理一致性的统计量、纹理反差的统计量、纹理熵的统计量以及纹理灰度相关性的统计量),将从所有已知材料提取的特征值保存到纹理特征库中,对于待检手写材料,同样采用灰度共生矩阵的方法提取其纹理特征,再利用最小欧氏距离分类法将从待检手写材料中提取的特征值与纹理特征库中的特征值进行比对,与欧氏距离比对值最小的相匹配,输出匹配成功的原材料的标号,进而识别出待检材料书写者的身份。
- 推荐网络例句
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I didn't watch TV last night, because it .
昨晚我没有看电视,因为电视机坏了。
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Since this year, in a lot of villages of Beijing, TV of elevator liquid crystal was removed.
今年以来,在北京的很多小区里,电梯液晶电视被撤了下来。
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I'm running my simile to an extreme.
我比喻得过头了。