While in the image normalization, the Bicubic interpolation method is used in it.
并采用双三次插值方法对图像大小归一化处理。
The geometrical invariant space is constructed by using image normalization. A significant region is obtained from the normalized image by utilizing the invariant centroid theory.
方案利用归一化技术将原始图像映射到几何不变空间内，结合不变质心理论提取出归一化图像的重要区域；
It was proved to be very good for improving the computing speed when a large number of image Windows have to be processed with grayscale distribution normalization.
实验证明，当需要对一幅图像的大量图像窗口进行灰度分布标准化时，这种算法对提高计算速度十分有效。
In writer identification (WI), writing styles are always compared by character matching, while image preprocessing and normalization are very important for matching.
笔迹鉴别多用匹配方法比较字符的书写风格，而字符图像的预处理和归一化对匹配是非常重要的。
Iris image preprocessing includes four parts: iris localization, iris normalization, iris image enhancement and choice of the valid region.
虹膜图像的预处理主要分为四步：内外边缘定位、图像归一化、图像增强和有效区域的划分。
Normalization of ear image has a very important significance in ear recognition, and provides precondition for later work.
人耳图像的归一化在人耳识别中具有相当重要的意义，为后续的工作提供了前提。
The preprocessing in an automatic fingerprint identification system usually includes five steps: normalization, directional graph computation, image segmentation, filtering and binarization.
指纹预处理一般包括规格化、方向图计算、图像分割、滤波、二值化等环节，该文系统地讨论了各环节的有效算法。
It is composed of iris localization, iris normalization, iris image enhancement and denoising in image preprocessing.
虹膜图像的预处理包括虹膜图像的定位、归一化、增强和去噪。
The image post-processing includes image connectivity processing, interference stripe suppression and centroid normalization.
图像后处理包括图像连通处理、干扰条纹抑制、图像质心归一化等。
Iris recognition system consists of image capturing, iris segmentation, iris normalization and enhancement, feature extraction and matching modules.
虹膜识别系统一般由图像采集、虹膜分割、归一化及图像增强、特征提取及编码和匹配识别几个部分组成。
Image preprocessing is usually consisted of following steps: quality assessment, mean filtering, gray normalization, gray equalization, the Oriental filtering, binarization as well as thinning.
指纹预处理一般包括以下几个步骤：图像质量评估、均值滤波、灰度归一化、灰度均衡化、方向滤波、二值化以及细线化。
The algorithm does not apply the traditional im - age normalization technique, so it guarantees watermarked image high transparency, that is to ensure high quality of watermarked image.
该算法不是采用传统的图像归一化技术，所以保证了水印图像的高透明性，即保证了嵌入水印后的图像的高质量。
The proposed method analyses local image statistics and then matches the local histograms of two images to be fused by applying mean or mean variance matching normalization functions.
该方法分析了局部影像统计特性，应用均值或均值—方差匹配正态函数，对要融合的两幅影像局部直方图进行匹配。
Besides, the paper focuses on the standardization of face image, the normalization and synthesis of multi-pose face image from a single view.
对其中的人脸图像标准化方法、归一化处理和由单视图生成多姿态人脸图像等关键技术进行了重点探讨。
Combining the thoughts of image intensity normalization and two-dimensional cross-entropy, a moving object detection algorithm, which is robust against illumination changes, is presented.
结合图像亮度归一化和二维交叉熵的思想提出了一种针对光照变化鲁棒性强的运动目标检测算法。
The first one is improper image pre-processing, such as segmentation, normalization and thinning, which lose the features of letters relationship and strokes.
其一是图像预处理方法不当，在字符切分、大小归一化、倾斜校正以及签名图像的细线化时会丢失签名特征。
Relative radiometric normalization of multi-temporal satellite images is the necessary process in change detection or image mosaic.
多时相遥感影像的相对辐射归一化是进行变化检测或拼接不可缺少的步骤。
An image pre-processing techniques based on Wiener filter and normalization of image brightness is proposed for weaken the influence of periodic noise and brightness variation.
提出维纳滤波与亮度归一化相结合的图像预处理技术，去除固定模式噪声和亮度变化的影响。
The preprocessing mainly focuses on image enforcement, geometry normalization of face images, image intensity normalization.
在人脸图像的预处理阶段，本文主要完成对人脸样本的图像增强、几何及灰度归一化工作。
After image localization and normalization, the subimage for each finger image is obtained.
对手指图像进行定位，经分割、归一化后得到了用于身份鉴别的手指子图。
After cropping eye area from binary face image, we use image-size normalization geometrical conditions to detect eyes.
截取二值人眼区域之后，利用图像尺寸归一化几何约束条件定位人眼。
This paper analyse the image enhancement, the binarization, the noise abatement, the thinning, the normalization and the feature extraction on the handwritten digit recognition.
本文首先对手写数字图像的图像灰度化、二值化、去噪、细化、归一化、特征提取等预处理过程进行分析；
This paper analyse the image enhancement, the binarization, the noise abatement, the thinning, the normalization and the feature extraction on the handwritten digit recognition.
本文首先对手写数字图像的图像灰度化、二值化、去噪、细化、归一化、特征提取等预处理过程进行分析；
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