A vision chip for color segmentation and pattern matching

Authors:
Ralph Etienne-Cummings;Philippe Pouliquen;M. Anthony Lewis
Affiliations:
Iguana Robotics, Urbana, IL and Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD;Iguana Robotics, Urbana, IL and Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD;Iguana Robotics, Urbana, IL
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2003

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Abstract

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 1mW. To our knowledge, this is the first chip that integrates imaging, color segmentation, and color-based object recognition at the focal plane.