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Counting objects in an image seems like an easy task, which can be automated through machine vision and image analysis, but it becomes difficult when objects touch, move randomly, or are hard to distinguish from their background.
LMI introduced the manufacturer to Cyth Systems, a leading integration and engineering firm headquartered in Southern California with pioneering success in designing and building automated test systems, machine vision systems, and embedded control systems.
Specifying a lens for an imaging system can seem like a complex task, so the key is breaking the selection down into manageable pieces.
Over the years, manufacturers of all types of products have deployed literally thousands of machine vision systems for applications such as assembly verification, gaging and motion guidance.
Image processing is usually done in order to extract information of interest from a busy image or to enhance the image.
Previously considered bulky, expensive and complex to interpret, machine vision technology has undergone continuous improvements to become an integral part of quality control for industrial or manufacturing production lines.
Bill Arbogast explains his perspective on quality, ISO 9001, and how to manage inevitable business changes.
Read: The 2013 Quality Professional of the Year
The purpose of this field guide is to assist organizations, step by step, in implementing a quality management system (QMS) in conformance with ISO 9001:2008, whether from scratch or by transitioning from ISO 9001:2000. It examines each sub-clause of Sections 4–8 of ISO 9001:2008, which contain the requirements, and gives a list of the documentation/documents required, internal audit questions, a summary of management’s responsibilities, and a flowchart of the steps that need to be undertaken to satisfy the requirements.
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