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Proceedings Paper

ColorCam: a color-based object recognition camera
Author(s): Ralph Etienne-Cummings; Philippe Pouliquen; M. Anthony Lewis
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Paper Abstract

A 128(H) x 64(V) x RGB CMOS imager is integrated with region-of-interest selection, RGB-to-HSI transformation, HSI-based pixel segmentation, 36-bins x 12bits HSI histogramming and sum-of-absolute-difference (SAD) template matching. 32 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 look-up 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 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 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 30fps, 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.

Paper Details

Date Published: 31 May 2005
PDF: 9 pages
Proc. SPIE 5783, Infrared Technology and Applications XXXI, (31 May 2005); doi: 10.1117/12.609469
Show Author Affiliations
Ralph Etienne-Cummings, Iguana Robotics (United States)
Johns Hopkins Univ. (United States)
Philippe Pouliquen, Iguana Robotics (United States)
Johns Hopkins Univ. (United States)
M. Anthony Lewis, Iguana Robotics (United States)

Published in SPIE Proceedings Vol. 5783:
Infrared Technology and Applications XXXI
Bjorn F. Andresen; Gabor F. Fulop, Editor(s)

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