说明：  山 东 大 学 硕 士 学 位 论 文：图像边缘检测算法的研究本 文 分 为 七 个 部 分 。第一部分首先阐述了课题的研究背景、意义以 及该领域的发展现状；第二部分介绍了几种经典的边缘检测方法，给出 了这些方法的图像边缘检测结果，并且进行了相关的分析比较；第三部 分阐述了BP 神经网络的结构以及数学模型等相关知识；第四部分具体 介绍了一种新的基于统计向量和BP 神经网络的边缘检测方法；第五部 分介绍了一种有效的边缘细化算法，它可以对新方法得到的图像边缘进 一步处理以达到边缘的准确定位；第六部分给出了新方法的实验结果并 且进行了相关分析。最后，本文在第七部分提出了研究展望以及后续研 究的主要内容。
(The paper is organized as following seven parts. Firstly, Section 1 gives an introduction of the background, significance and development of the field of edge detection. And Section 2 introduces several classic edge detectors and gives edge detection results of these methods and offers some relative analysis and comparison. Then Section 3 offers specific knowledge about the architecture and mathematical model of the BP neural network. The specific algorithm and architecture of the proposed new edge detector based on the statistical vector and the BP neural network are introduced in Section 4. And an effective algorithm of edge thinning which is helpful for accurate edge localization is offered in Section 5. Experimental results and analysis of the performance of the new edge detector are presented in Section 6. At last, the paper ends with some further research plans mentioned in Section 7.)