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Omnidirectional vision sensors provide a large field of view for numerous technical applications. But the original images of these sensors are distorted, not simply interpretable and not easy to apply for normal image processing routines. So image transformation of original into panoramic images is necessary using various projections like cylindrical, spherical and conical projection, but which projection is best for a specific application? In this paper, we present a novel method to evaluate different projections regarding their applicability in a specific application using a novel variable, the pixel density. The pixel density allows to determine the resolution of a panoramic image depending on the chosen projection. To achieve the pixel density, first the camera model is determined based on the gathered calibration data. Secondly, a projection matrix is calculated to map each pixel of the original image into the chosen projection area for image transformation. The pixel density is calculated based on this projection matrix in a final step. Theory is verified and discussed in experiments with simulated and real image data. We also demonstrate that the common cylindrical projection is not always the best projection to rectify images from omnidirectional vision sensors.

IMAGE RECTIFICATION - Evaluation of Various Projections for Omnidirectional Vision Sensors using the Pixel Density