Toward intelligent manufacturing: label characters marking and recognition method for steel products with machine vision

Correctly coding materials and identifying characters marked on materials are very important for steel manufacturing industry to realize informatization management and intelligent manufacturing. However, the steel products manufacturing is often in a high temperature environment, and there are a lot of material storage and retrieval processes, workers are not easily close to the environment and complete tasks, so it is a great challenge to automatically mark and identify characters on the steel products. This paper presents a framework of label characters marking and management for steel materials, furthermore, a kind of marked characters online detection and tracking method has been provided based on machine vision. In addition, some experiments have been done in BaoSteel to mark characters on hot billets and recognize them in multi situations, and the results show that the proposed method is practical, and has provided a helpful exploration in obtaining accurate fundamental data for the intelligent manufacturing system in steelworks.     

Pattern recognition,image processing and computer vision in fifth generation computer systems

It is well-known that one of the goals of research for the last two decades or so in pattern recognition and its sub-areas, such as processing, analysis and understanding of image, speech and natural language, and computer vision techniques etc., has always been to develop fundamental techniques for flexible interactive intelligent man-machine interfaces for computers. In this paper, the author tries to argue that for the evolution of fifth generation computer systems (FGCS) as defined by Japanese scientists, some of the things required are realisation and implementation of the advances in pattern recognition and its sub-areas, not only to achieve the man-machine interface with a natural mode of communication, but also for the realisation of the basic mechanisms of inference, association and learning, which are inherent both in pattern recognition and in the core functions of FGCS. The next generation computers will be knowledge-based systems, which form a subdomain of artificial intelligence (a1) techniques, and soa1 provides the essential link between pattern recognition domains and different application systems. No attempt is made to discuss other essential conceptual building blocks, such as software engineering, computer architecture and very large scale integration technology unless these become very relevant in the discussions of concerned topics of the paper. A section on limitations of perception, learning and knowledge for computing machines is also included. This work was funded by the Knowledge-based Computer Systems Project of the Department of Electronics, Government of India.