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This paper will describe PIPE® and how its capabilities can be used for inspection applications. PIPE is a high performance parallel processor with an architecture specifically designed for the processing of video images at up to 60 fields per second. The unit is modular and programmable. It processes sequences of images through a pipeline of point processors, image buffers and arithmetic or Boolean neighborhood operators.There are multiple data pathways between the stages in forward, recursive and backward directions that allow images to interact in many useful ways. Due to its architecture, PIPE inherently allows the processing of many images simultaneously for working with dynamic scenes or multiple combinations of the same image. Although originally designed for robot guidance applications, PIPE has many features that make it well suited for use in inspection. For these inspection applications, this multiple image capability allows the pipelining of different processes on different images at the same time. In addition, a programmable region of interest capability allows different processes to be run on different areas of the same image. Illustrations of some these techniques will be presented. SPIE Vol. 730 A utomated Inspection and Measurement (1986) / 15Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/27/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

Image flow, the apparent motion of brightness patterns on the image plane, can provide important visual information such as distance, shape, surface orientation, and boundaries. It can be determined by either feature tracking or spatio-temporal analysis. We consider spatio-temporal methods, and show how differential range can be estimated from time-space imagery.We generate a time-space image by considering only one scan line of the image obtained from a camera moving in the horizontal direction at each time interval. At the next instant of time, we shift the previous line up by one pixel, and obtain another line from the image. We continue the procedure to obtain a time-space image, where each horizontal line represents the spatial relationship of the pixels, and each vertical line the temporal relationship.Each feature along the horizontal scan line generates an edge in the time-space image, the slope of which depends upon the distance of the feature from the camera. We apply two mutually perpendicular edge operators to the time-space image, and determine the slope of each edge. We show that this corresponds to optical flow. We use the result to obtain the differential range, and show how this can be implemented on the Pipelined Image Processing Engine (PIPE).We use a simple technique to calibrate the camera and show how the depth can be obtained from optical flow. We provide a statistical analysis of the results of 3-D reconstruction of the scenes using optical flow determined from 3x3, 5x5, and 7x7 edge operators.

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