<title>Adaptive ray casting (ARC) algorithm for simulation of machine vision systems</title>

Abstract

Optical sensor simulations based on high fidelity models of illumination, scenes, cameras, and signal processors can accurately predict the performance of machine vision systems. These simulations typically render images of the scene from solid models that define each object in the sensor's field of view by a ray casting algorithm, then pass the image through models of the camera (receiver) and the signal processor. Conventional ray casting algorithms cast a uniformly spaced grid of rays toward the scene from the camera and add the returns computed for each ray to the appropriate pixel of the image. This paper describes an adaptive ray casting (ARC) algorithm that dynamically adjusts the resolution of the ray grid, within bounds set by the user, to match the level of detail present in each part of the image. The ARC Algorithm generates a resolution map for the scene specifying the resolution required in each pixel, then it dynamically adjusts the spacing of the ray grid to match the required resolution during the rendering process. The resolution map is stored in the same array as the image, allowing the algorithm to run efficiently on systems with limited memory. This ARC Algorithm renders images of very high fidelity without extreme execution times.