Eccentricity Compensator for Wide-Angle Fovea Vision Sensor
Sota Shimizu* and Joel W. Burdick**
*California Institute of Technology, Division of Biology, MC 139-74, Pasadena, CA 91125, USAWaseda University, Advanced Research Institute for Science and Engineering, 17 Kikui-cho, Shinjuku-ku, Tokyo 162-0044, Japan
**California Institute of Technology, Department of Bioengineering
This paper aims at the acquisition of a robust feature for rotation, scale, and translation-invariant image matching of space-variant images from a fovea sensor. The proposed model eccentricity compensator corrects deformation in log-polar images when the fovea sensor is not centered on the target image, that is, when eccentricity exists. An image simulator in a discrete space implements this model through its geometrical formulation. This paper also proposes Unreliable Feature Omission (UFO) using the Discrete Wavelet Transform. UFO reduces local high frequency noise appearing in the space-variant image when the eccentricity changes. It discards coefficients when they are regarded as unreliable, based on digitized errors in the input image from the fovea sensor. The first simulation estimates the compensator by comparing it with other polar images. This result shows the compensator performs well, and its root mean square error (RMSE) changes only by up to 2.54% on the condition that the eccentricity is within 34.08°. The second simulation shows UFO performs well for the log-polar image remapped by the eccentricity compensator when white Gaussian noise (WGN) is added. The result from the Daubechies (7, 9) biorthogonal wavelet shows UFO reduces the RMSE by up to 0.40 %, even if the WGN is not added, when the eccentricity is within 34.08°.
This paper is the full translation from the transactions of JSME Vol.73, No.733.
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