预处理包括图纸扫描输入、图象二值化、图象平滑与去噪、线条细化和曲线跟踪。
The preprocessing steps include drawing scanning, binary image transforming, line thinning and cure tracing.
该方法避免了一些传统汉字特征提取方法需要对图象进行二值化操作而造成的汉字字符结构信息丢失。
As a result, the proposed method avoids the binary operation used in some traditional Chinese character feature extractions that will seriously destroy the Chinese character structure.
然后建立去除复杂实际背景和自适应二值化的动态图象预处理模型，并根据矩法搜索和求取目标质心；
Secondly, Deleting background model and binarization model are established, and the mass center of object is searched and computed based on method of moment.
在图象处理算法中，应用图象全局二值化方法、字符“有效行”特征的提取和双BP神经网络，对手写体字符的识别取得了良好的效果。
With the way of binarization by globe threshold, the extracting mathod of "effective-rows" feature of handwriting numerals and recognition mathod of two parallel BP networks, good result is acquired.
并根据金属图象分析要求，提出了先二值化金属图象再进行边缘提取的方法。
Furthermore, a new method of metal image edge detection was presented by binary image.
在方向图和脊线频率的基础上，实现了一种基于脊线方向分析的方法对指纹图象进行二值化；
We also improve on the binarization method of fingerprint images based on the 2nd derivative by the orientation and ridge frequency of the images.
第一种方法采用动态门限检测指纹的隆线，直接给出二值化象图。
The first method adopts dynamic threshold to detect the threads of finger-print, and gives the bilevel image directly.
给出了一种基于图象灰度分布统计特征期望值为阈值的二值化方法。
This paper presents an algorithm for threshold employing gray level arithmetic mean based on relevant conception in probability theory.
给出了一种基于图象灰度分布统计特征期望值为阈值的二值化方法。
This paper presents an algorithm for threshold employing gray level arithmetic mean based on relevant conception in probability theory.
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