文档介绍：南京航空航天大学
硕士学位论文
基于细胞神经网络的图像边缘提取算法研究
姓名:黄蕾
申请学位级别:硕士
专业:测试计量技术及仪器
指导教师:刘文波
20060101
南京航空航天大学硕士学位论文
摘要
边缘是图像中重要的特征之一,是计算机视觉、模式识别等研究领域的重
要基础。N)是一种并行处理器,在图像处理上有很大的发展
空间。
N 提取图像边缘的过程,给出了所设计的二值图像算
法的流程图。利用设计出的网络参数,对二值图像进行了边缘提取,提取结果
表明该网络参数是合理的。在二值图像的基础上,实现对灰度图像的边缘提取,
改进了前人提出的分 8 层的算法,给出了一组灰度图像的边缘提取的结果,结
果表明改进的算法是更加有效的。
N 的算法与传统的算法对图像边缘处理的仿真模型,两者比
N 的算法在硬件实现上能够高速并行计算,且处理速度与图像大
小无关,所以能够实现图像的实时处理,不失为一种有效的应用方法。
N 的图像边缘提取的模板取值范围,在确定范围内对图像进
行了验证,结果表明该范围是正确的。在此基础上,深入分析了灰度图像的模
板取值,推导了模板取值和其像素值之间的关系,从而确定了灰度图像的自适
应模板。
最后,对该算法进行了基于 FPGA 的硬件实现。N 的边缘
提取算法的实现方法,并给出了实验结果,结果表明这种方法是切实可行的。

N,边缘提取,算法,模板取值,FPGA

I
基于细胞神经网络的图像边缘提取算法研究
ABSTRACT
Edge is one of the important characteristics of image, and it also is the element
of several research areas, puter vision and pattern
work (CNN) is a parallel processor. In the erea of image processing, the
CNN has a broad developing space.
The dissertation firstly introduces the process of edge detection based N
and supplies the flow chart of binary image arithmetic designed. work
parameters are used to detect the image edge. The detection results show these
parameters are suitable. Meanwhile, on the basic of binary image, the detection of
gray-scale image is realized by the modified eight-level arithmetic. The tetection
results also show the modified arithmetic is more effective.
The two simulation models for image edge detection based N arithmetic
and traditional arithemestic respectively are designed. Compared the two simulation
results, N arithemetic has several advantages: high speed parallel calculation
on hardware, calculation speed is independent of image size, real-time detect image
edge. Therefore, the arithmetic N is an effective method.
Then, the value range N model is presented, the results used these values
show it is correct. On this base, the value range of gray image is analysised deeply.
The relation between Model value an