山东建筑大学毕业设计外文文献及译文本科毕业设计外文文献及译文文献、资料题目：Food Handling Using Computer 文献、资料来源：文献、资料发表（出版）日期：2008.12 院 （部）： 机电工程学院专 业： 机械工程及自动化班 级： 机械054姓 名： 刘翠芹学 号： 2005071222指导教师： 董明晓教授翻译日期：2009.5.15山东建筑大学毕业设计外文文献及译文外文文献：Food Handling and Packaging using Computer vision and RobotAbstractEven though the use of robot vision system in manufacturing sectors is now a commonplace, however, the technology embodied in these devices is poorly matched to industrial needs of food processors. In particular, food processing imposes special demands upon machinery. For instance the vision sensor must be programmed to detect the position of single and isolated object as well as overlapping or occluding objects. Special grippers have to be designed for handling of food articles such that they have minimum contact with the food items and hence causing minimum damage to them. In this project, started over a year ago, a vision guidance system is being developed to meet this objective. The system integrates the modified version of the Hough transform algorithm as the main recognition engine. The methods and procedures were tested on commercially produced beef burgers. 1. IntroductionFrom the incoming down to the packaging lines, locating, recognizing and handling food objects are very important in food processing industry. These tasks are performed routinely in food industry mainly for quality evaluation and product classification. Such tasks are very laboriously demanding and tend to rely heavily on role of the human operator 1. Hands of workers using raw materials of animal origin can heavily be contaminated with faecal and other micro-pathogenic organisms 2. The study by Trickett 3 has shown a strong link between food poisoning and the hygiene standards of food processors. Complete automation of food handling and packaging by means of robotic arm is the most effective means to eliminate influence of manual handling of microbiological quality of foods.Robots have successfully been applied in a wide range of food industries primarily dealing with well-defined processes and products not only because they are relatively clean and hygienic, also because of their flexibility, ruggedness and repeatability. This trend will continue to grow with the increasing scrutiny and regulatory enforcements such as and Hazard Analysis and Critical Control Points (HACCP) together with companies that are looking for ways to decrease or eliminate worker exposure to repetitive motion tasks and harsh environment. However there are problems and challenges associated with the use of robots in food industry 4.Firstly the food products, despite of the same type, differ in size, shape and other physical variables. This imposes special demands for machinery to handle them,requiring multiple sensory, manipulation and environmental capabilities beyond those available in robots designed to automate manufacturing tasks. Secondly the success of applying robots for food handlers, hinges upon the success of detecting, locating, recognizing and handling severely overlapping and occluding cases of similar food objects. Thirdly, food objects are often delicate and usually covered with either slippery or viscous substances, making high speed handling of such targets a very challenging task. The existing contact-based mechanisms such as the vacuum suctioning and the clamp gripping are not applicable because they can potentially cause injuries and bruising to food products. Hence further research is needed in order to solve these problems. This paper addresses some of the problems, focusing on the methods used to control the robot directly from the vision sensor, attempting to simulate the way that humans use their eyes to naturally control the motion of their arms. 2. Materials and Methods 2.1 Sample Preparation The chosen food for this study is a locally produced beef-burger. It possesses all the important characteristics which are unique to food products, such that they are very fragile and easily deformed. The average size of the beef-burgers is 8.5 mm in thickness and 46.1 mm radius and 69.3 gm in weight. Surface images of test samples were acquired using 8-bit robot vision system with uniform white background. The white background provides excellent contrast between the burger and the background. The chosen exposure was adjusted so that the image intensity histograms were approximately centered at mid-way of the full-scale range. The focal distance was selected to allow single as well as multiple samples to fit in the image frame. 2.2 Robot vision The robot vision systems used in this study is the Adept Cobra 600 4-DOF articulated scara robot, manufactured by Adept Tech., USA and equipped with Adept Vision Interface, MV-5 Adept controller and TM1001 CCD monochrome camera manufactured by Pulnix Inc., Canada. The camera was mounted onto link 2 of robot arm and illuminated using the wa