【作者】 何超；

【导师】 戴连奎；

【作者基本信息】 浙江大学 ， 模式识别与智能控制， 2003， 硕士

【摘要】 视觉系统是机器人系统中非常重要的组成部分。机器人视觉系统主要包括数字图像的获取、图像的预处理、特征提取和图像识别几部分。在数字图像获取部分，机器人周围的场景通过光学成像和数字化被转换成数字图像；在预处理阶段，系统通过几何变换、图像调整等对数字图像进行初步的调整，使之成为易于识别和处理的图像；在特征提取部分，系统对图像进行抽象化；在识别部分，系统对图像特征进行处理，进而在图像中找出需要识别的目标，确定其身份并进行定位。 通过对以往图像处理方法中图像分割和识别方法的研究，同时针对机器人足球系统的应用实际，本文对现有的用于机器人足球视觉系统的彩色图像分割和识别方法进行了剖析，并提出了相应的改进方法。论文的主要研究工作具体包括： 1．通过大量阅读中外文献，对现有的图像分割、特征提取和足球机器人系统中目标识别的方法有了较为全面和系统的了解。 2．根据足球机器人系统中视觉系统的实际应用环境，分析对比了不同颜色空间的优缺点，采用YUV颜色空间作为视觉系统的工作空间，从而减弱了光照变化对视觉系统带来的影响。 3．针对足球机器人系统中对视觉系统实时性方面的具体要求，提出了一种改进了阈值向量彩色图像分割方法，对于一个未知颜色的像素点，一次计算就能够判断其颜色，并将其进行分类。这种方法大大减少了视觉系统的工作量，提高了系统的实时性。 4．针对足球机器人系统中视觉系统现有的识别算法普遍需要对已经进行了颜色分类的像素点进行二次扫描，占用大量时间的缺点，提出了基于网格查找的新方法，并且这种网格查找与像素点的颜色分类同时进行，并不占用处理时间。 5．研究了多种不同的足球机器人小车顶部的色标标识方法，比较了不同的表示方法对识别的影响，提出了利用队标(TeamColor)同时进行位置和角度识别，利用队员标(IDColor)进行正方向标定的方法，实际应用表明该方法具有较高的识别精度。 6．将改进的阈值向量彩色图像分割方法用于彩色图像中的人脸检测，获得了良好的检测效果。更多还原

【Abstract】 Vision system is an important part in a robot system. Functionally, a robot vision system contains the following processes: the obtaining of digital image, the image pre-processing, character extraction and image identification. To obtain digital image, the environment around robot is captured by optical lens and then digitized into a digital image; then the digital image will be adjusted by using geometrical transform and image transform, which will be easier to be identified and processed, and some important characters will be abstracted; finally the vision system find out the target based on the processed image.Based on existing technology in image segmentation and identification, this thesis compared some common used algorithms, and proposed some improved algorithms. The main contributions include:1. Review the development of image segmentation and character extraction in image process and particularly in robot soccer system.2. For the application environment of robot soccer system, and to meet the need of the robot soccer system, this thesis analyzed some different color spaces, and selected YUV color space as the work space of the vision system, in which the disturb of the change of illumination is minimized.3. To meet the real-time demand in the robot soccer competition, this thesis proposed a color image segmentation method using improved threshold vector algorithm in YUV color space. The new algorithm can classify 8 colors in one time, so the speed of the algorithm is improved a lot.4. Most existing identification algorithms used in robot soccer vision system need to scan the image another time after all the pixels’ color have been classified, which is time consuming. In order to save time, a seed-fill algorithm based on grid search is introduced in this paper. The new algorithm is much faster.5. After compared some different types of color label in robot soccer system, which have different effects on vision identification. This thesis designed a new color label. In the new color label, the angle identification only depends on TeamColor, and the new color label is easier to be identified.6. Applied the improved color image segmentation method to human face detection in color image.更多还原