计算机应用论文角点检测及其在纤维识别中的应用研究.doc

角点检测及其在纤维识别中的应用研究 角点检测及其在纤维识别中的应用研究 research on the corner detection algorithm and application for identifying fibre【中文摘要】 角点检测问题是计算机图像处理领域的一个基础问题,是图像处理领域的一个重要研究方向。角点是图像的重要特征,在目标识别、视觉匹配和运动估计等领域都有重要的应用。本文提出了alfm角点检测算法,并根据大量实验统计分析和角点评价准则对该算法进行了评估,与harris角点检测算法相比,alfm角点检测算法能获得更好的角点检测效果,具有更强的检测性能。对物体的形态分析和描述是计算机视觉领域中的重要研究方向。在图像处理领域中,骨架包含了物体形态的重要信息,是形态描述的重要表示,在形态分析和模式识别中已经得到了广泛应用。基于骨架的形状目标识别方法是基于形状的检索技术的重要方面。骨架是一种简洁、直观的目标表示方法,它综合利用了目标的外部轮廓和内部区域信息,全面描述了目标形状的二维本质。与骨架相比,近似骨架的组合更加简单,因为它比骨架的结点和弧都要少,且近似骨架的结点和弧都是由线段组成,因此对于边缘长度的查询执行简单且计算速度快,使得需要实时处理的棉麻纤维识别系统成为可能。在异形纤维识别过程中,为了对不同类型的异形纤维进行分类,需要根据异形纤维的角点提取其近似骨架,然后在近似骨架(ss)的基础上进行语义分析和匹配识别。本文提出了alfm角点检测算法和基于ss的异形纤维识别算法并将其应用于异形纤维识别系统中,并与基于svm的识别分类算法进行对比分析。实验结果表明与不倾斜(即不存在变形和扭曲情况)的异形纤维相比,本文算法与svm的正确识别率基本相近,而对于存在变形和扭曲情况的异形纤维,本文算法的纤维识别率存在明显优势。因此,本文算法更适用于异形纤维识别系统【英文摘要】 corner detection is a basic problem in the field of image processing, which is an important method of low level image processing.corners are important image features that may be used at subsequent levels of computer vision such as object recognition,stereo matching and motion estimation.this paper provides an alfm corner detection algorithm which is estimated with numbers of experiments and corner criteria. compared with harris corner detection algorithm,alfm corner detection algorithm gains better results and stronger robusticity.modality analysis and description are important methods in computer vision.and in the field of image processing,skeleton which includes important information of the object modality is broadly used in the fields of modality analysis and pattern recognition.the shape object recognition method based on skeleton is an important aspect of detection methods based on shape.skeleton which is a simple and intuitionistic object description method uses the information of inner and outer region and roundly describes the planer essence of object shape.compared with the skeleton,because approximate skeleton contains fewer nodes and arcs and its nodes and arcs are made up of lines,the structure of approximate skeleton is simpler and faster to query the edge length,which made the real-time fiber recognition system feasible.in the abnormity fiber recognition system,we need to calculate the approximate skeleton according to the corner and deal with the fiber recognition based on the approximate skeleton.two algorithms,the alfm corner detection algorithm and the abnormity fiber recognition algorithm based on ss,are provided in this paper.the results of experiment suggest that their recognition rates are similar to normal fiber,but the recognition rate of the algorithm proposed by this paper is better to gradient fiber than the svm recognition algorithm.as a result,the algorithm proposed in this paper is more appropriate to the real-time fiber recognition system. 【中文关键词】 角点检测; 最小二乘法; 协方差矩阵; 特征向量; 滑动窗口; 近似骨架; delaunay三角剖分 【英文关键词】 corner detection; least square; covariance matrix; eigenvector; gliding window; approximate skeleton; delaunay triangulation 【毕业论文目录】摘要 5-7 abstract 7-8 1 绪论 11-23 1.1 研究目的及意义 11-12 1.2 国内外研究状况概述 12-21 1.3 本文主要内容和结构安排 21-23 2 系统综述 23-28 2.1 纤维自动识别系统 23-26 2.2 角点检测算法在系统中的应用 26 2.3 角点检测算法的难点 26 2.4 基于近似骨架的异形纤维识别算法在系统中的应用 26 2.5 基于近似骨架的异形纤维识别算法的难点 26 2.6 本章小结 26-28 3 alfm角点检测算法 28-39 3.1 角点检测准则 29 3.2 alfm角点检测算法 29-36 3.3 实验与结论 36-39 4 基于近似骨架(ss)的异形纤维图像识别 39-64 4.1 模式识别技术简介 39-42 4.2 基于形状的图像检索技术简介