We describe a practical and precise calibration method for generating a top view image that is transformed so that a planar object such as the road can be observed from a direction perpendicular to its surface. The geometric relation between the input and output images is described by a 3 3 homography matrix. Conventional methods use large planar calibration patterns to achieve precise transformations. The proposed method uses much smaller element patterns that are placed in arbitrary positions within the view of the camera. One of the patterns is used to obtain an initial homography. Then, the information from all of the patterns is used by a non-linear optimization scheme to reach a global optimum homography. The experiment done to evaluate the method showed that the precision of the proposed method is comparable to that of the conventional method where a large calibration pattern is used, making it more practical for automotive applications.

We proposed a new method to evaluate display legibility as a function of resolution. This method was able to evaluated display legibility without being restricted to the display resolution. Using this method, subjective psychological experiments were carried out to investigate display resolution, which provides legibility, in observing small characters. Samples viewed by subjects were images displayed on a high-resolution TFT-LCD that we developed, CRT images and printed documents for comparison. We have found that TFT-LCD legibility was much better than that of CRT, and that minimum resolution of about 175 dpi was needed for use in legible document viewers.

In this article, we present a new image-stabilization technology for still images based on blind deconvolution and introduce it to a consumer digital still camera. This technology consists of three features: (1)double-exposure-based PSF detection, (2)efficient image deblurring filter, and (3)edge-based ringing reduction. Without deteriorating the deblurring performance, the new technology allows us to reduce processing time and ringing artifacts, both of which are common problems in image deconvolution.