Dual camera based wide-view imaging system and real-time image registration algorithm

For high speed visual inspection in semiconductor or flat panel display industries, it is essential to acquire two-dimensional images on regions of interests with a large field of view (FOV) and a high resolution simultaneously, but two points are usually conflicting. In this paper, an imaging system is newly proposed to achieve high quality image in terms of precision and FOV, which consists of single imaging lens, dual camera sensors, a beam-splitter, and a synchronous frame grabber. To simplify multiple lens system into single lens system help multiple images registered into final single image without big computational burden. For simultaneously acquired object images from two camera sensors, Zhang's camera calibration method is applied to calibrate each camera first of all. Secondly, to find a mathematical mapping function between two images acquired from different view cameras, the matching matrix from multiview camera geometry is calculated based on their image homography. Through the image homography, two images are finally registered to secure a large inspection FOV. Here the inspection system of using multiple images from multiple cameras need very fast processing unit for real-time image matching. For this purpose, parallel processing hardware and software are utilized, such as Graphics Processing Unit (GPU) and Compute Unified Device Architecture (CUDA). As a result, we can obtain a matched image from two separated images in real-time within 20msec. Finally, the acquired homography is evaluated in term of accuracy through a series of experiments, and the obtained results shows the effectiveness of the proposed system and method.