A Vision Chip for Color Segmentation and Pattern Matching
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A Vision Chip for Color Segmentation and Pattern Matching Ralph Etienne-Cummings Iguana Robotics, P.O. Box 625, Urbana, IL 61803, USA Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA Email: [email protected]
Philippe Pouliquen Iguana Robotics, P.O. Box 62625, Urbana, IL 61803, USA Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA Email: [email protected]
M. Anthony Lewis Iguana Robotics, P.O. Box 625, Urbana, IL 61803, USA Email: [email protected] Received 15 July 2002 and in revised form 20 January 2003 A 128(H) × 64(V) × RGB CMOS imager is integrated with region-of-interest selection, RGB-to-HSI transformation, HSI-based pixel segmentation, (36bins × 12bits)-HSI histogramming, and sum-of-absolute-difference (SAD) template matching. Thirty-two learned color templates are stored and compared to each image. The chip captures the R, G, and B images using in-pixel storage before passing the pixel content to a multiplying digital-to-analog converter (DAC) for white balancing. The DAC can also be used to pipe in images for a PC. The color processing uses a biologically inspired color opponent representation and an analog lookup table to determine the Hue (H) of each pixel. Saturation (S) is computed using a loser-take-all circuit. Intensity (I) is given by the sum of the color components. A histogram of the segments of the image, constructed by counting the number of pixels falling into 36 Hue intervals of 10 degrees, is stored on a chip and compared against the histograms of new segments using SAD comparisons. We demonstrate color-based image segmentation and object recognition with this chip. Running at 30 fps, it uses 1 mW. To our knowledge, this is the first chip that integrates imaging, color segmentation, and color-based object recognition at the focal plane. Keywords and phrases: focal plane image processing, object recognition, color histogramming, CMOS image sensor, vision chip, VLSI color image processor.
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INTRODUCTION
CMOS-integrated circuits technology readily allows the incorporation of photodetector arrays and image processing circuits on the same silicon die [1, 2, 3, 4, 5, 6]. This has led to the recent proliferation in cheap and compact digital cameras [7], system-on-a-chip video processors [8, 9], and many other cutting edge commercial and research imaging products. The concept of using CMOS technology for combining sensing and processing was not spearheaded by the imaging community. It actually emerged in mid ’80s from the neuromorphic engineering community developed by Mead and collaborators [10, 11]. Mead’s motivation was to mimic the information processing capabilities of biolog-
ical organisms; biology tends to optimize information extraction by introducing processing at the sensing epithelium [12]. This approach to sensory information processing, which was later captured with terms such as “sensory processing” and “computational sensors,” produced a myriad v
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