摄像机目标定位模型

对摄像机固定进行目标定位,提出了一种简单可行模型.利用仿射变换,通过简单的几何关系为定位问题提供一种全新的思路.     

计算机视觉中传统摄像机定标方法综述

根据定标物和定标算法的不同,对现有的各种传统摄像机定标方法进行了总结、比较和分类,并讨论了各种传统定标方法在计算机视觉中的应用特征,提出今后有待进一步研究的方向.     

基于折光鱼眼全景相机的双目立体视觉标定

面向鱼眼立体视觉系统标定,针孔等传统成像模型对高畸变镜头建模存在不准确问题,本文基于统一球面投影机理,建立了折光鱼眼全景相机的双目立体视觉投影模型,并对此双目立体视觉系统进行了标定。标定过程中,首先利用Hough变换实现了全景图像中角点的精确检测,在此基础上,利用Levenberg—Marquardt(L-M)法对相机内、外参数进行精细化估计,从而实现相机的准确标定。相对于传统的双目鱼眼相机标定法,通过对比实验验证了双目立体视觉标定方法的优越性。     

Integrated color defect detection method for polysilicon wafers using machine vision

For the typical color detects of polysilicon wafers, i.e., edge discoloration, color inaccuracy and color non-uniformity, a new integrated machine vision detection method is proposed based on an HSV color model. By transforming RGB image into three-channel HSV images, the HSV model can efficiently reduce the disturbances of complex wafer textures. A fuzzy color clustering method is used to detect edge discoloration by defining membership function for each channel image. The mean-value classi- fying method and region growing method are used to identify the other two defects, respectively. A vision detection system is developed and applied in the produc- tion of polysilicon wafers.     

基于特征的大尺寸零件序列局部视觉测量方法

为了实现常规尺寸和大尺寸机械零件的视觉测量,提出一种新的基于序列局部图像尺寸特征的测量方法.不进行图像拼接,而是提取序列局部图像的尺寸特征,并以图像序列之间的关联关系为依据求解零件尺寸.针对影响测量精度的相面旋转问题,充分利用工件表面纹理信息,提出了基于纹理特征的序列局部图像校准方法,获得序列图像之间的相对旋转角度,解决了测量过程中相机抖动或零件旋转引起的尺寸特征方向变动问题.通过实例说明了所提方法的实现过程及其有效性.实验表明,对大尺寸零件采用序列图像测量法,相对测量误差在0.012%以内,满足板类零件的精密测量要求.     

Automatic recognition method for optical measuring instruments based on machine vision

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope (UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation (BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dynamically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.     

Prediction of shelled shrimp weight by machine vision

The weight of shelled shrimp is an important parameter for grading process. The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness. In this paper, a multivariate prediction model containing area, perimeter, length, and width was established. A new calibration algorithm for extracting length of shelled shrimp was proposed, which contains binary image thinning, branch recognition and elimination, and length reconstruction, while its width was calculated during the process of length extracting. The model was further validated with another set of images from 30 shelled shrimps. For a comparison purpose, artificial neural network (ANN) was used for the shrimp weight predication. The ANN model resulted in a better prediction accuracy (with the average relative error at 2.67%), but took a tenfold increase in calculation time compared with the weight-area-perimeter (WAP) model (with the average relative error at 3.02%). We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.      

基于机器视觉的车道标志线检测研究

针对车辆辅助驾驶或自主驾驶中的车道保持问题, 研究了基于视觉的车道标志线实时检测方法. 介绍了系统组成、工作原理和车道模型, 并着重讨论了车道图像的检测算法. 其主要思想是在图像上选取几个合适的处理区域, 通过对每个处理区域进行适当的预处理、边缘检测和霍夫变换等过程来提取车道描述特征. 试验结果表明, 该方法具有实时性好、识别可靠性高等特点, 在一定程度上能为后续的辅助驾驶或自主驾驶提供决策依据.     

基于机器视觉的瓷砖尺寸检测研究

以瓷砖尺寸的检测为研究对象,研究了基于机器视觉的瓷砖尺寸检测。根据瓷砖的国家标准,利用机器视觉传感器,对采集图像进行降噪和图像增强,构建了一套瓷砖尺寸在线检测装置,并对该装置进行试验验证。结果表明,机器视觉对瓷砖尺寸检测达到国家标准和企业标准。