虹膜图像中通常包含了干扰因素的眼睑，为了消除影响识别效果的这种干扰因素，保证较高的识别率，提出一种分段检测算法。
In order to ensure high recognition rate and remove the disturbing factor in iris image, an algorithm of segment detection is proposed to detect eyelid and remove it.
为了解决这个问题，提出了一种新的频率估计算法，采用扩频调制信息消除策略和分段相关FFT频谱分析技术实现频偏精确估计。
To solve this problem, a new method of frequency offset estimation is proposed. This method adopts modulated data elimination technique and the segmental correlation FFT algorithm.
为此，需要消除PC G信号中的噪声，并用分段算法定位第一心音。
To achieve this, noise in the PCG signal should be removed, and a segmentation method should be used to locate the first heart sound.
该方法采用自适应高斯滤波器对原始曲线进行平滑处理以消除噪声影响，并提出了一种适合于圆弧曲线拟合的分段算法。
This method adopts self-adaptive gauss filter to process original curve smoothly to eliminate noise effects, and proposes a fragrmented algorithm that is adaptive to circular arc.
为此，本文用非线性分段色彩变换方法对光照造成的高光和阴影影响进行消除，部分解决了人脸图象上存在的高光和阴影影响问题。
Nonlinear color transformation is used to eliminate the influence of highlight and shadow so that the highlight and shadow of face image are resolved partly.
有重叠区的多点分段成形可减缓强制变形区与过渡区交界处的曲率突变现象，但未完全消除剧烈的塑性变形。
The sectional forming method with overlapping area can restrict the variety of curvature, but the drastic distortion is not removed.
有重叠区的多点分段成形可减缓强制变形区与过渡区交界处的曲率突变现象，但未完全消除剧烈的塑性变形。
The sectional forming method with overlapping area can restrict the variety of curvature, but the drastic distortion is not removed.
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