In this paper, we propose a new method that can remove view-disturbing noises from stereo images. One of the thorny problems in outdoor surveillance by a camera is that adherent noises such as waterdrops on the protecting glass surface lens disturb the view from the camera. Therefore, we propose a method for removing adherent noises from stereo images taken with a stereo camera system. Our method is based on the stereo measurement and utilizes disparities between stereo image pair. Positions of noises in images can be detected by comparing disparities measured from stereo images with the distance between the stereo camera system and the glass surface. True disparities of image regions hidden by noises can be estimated from the property that disparities are generally similar with those around noises. Finally, we can remove noises from images by replacing the above regions with textures of corresponding image regions obtained by the disparity referring. Experimental results show the effectiveness of the proposed method.

A method for locating underground pipes from a pulse radar image is presented. The method employs the Laplacian of Gaussian filter to extract edges and employs the Hough transform to determine the depth of the pipes. A preliminary experiment showed its ability to detect deeply buried pipes with weak signal echoes.

In this paper, we propose a new region extraction method with a chromakey technique using a two-tone striped background. A chromakey compositing is a technique for separating actors or actresses from a background, and then compositing a different background. The conventional chromakey technique usually uses an unicolored blue or green background, and has a problem that one's clothes are regarded as the background if their colors are same with the background's color. Therefore, we use two-tone striped background and utilize the adjacency condition between two-tone striped areas on the background to extract the foreground regions whose colors are same with the background. The procedure of our proposed method consists of four steps: 1) background color extraction, 2) striped region extraction, 3) foreground extraction, and 4) image composition. As to the background color extraction, the color space approach is used. As to the striped region extraction, it is difficult to extract striped region by a color space approach because the color of this region may be a composite of two background colors and different from them. Therefore, the striped region is extracted from adjacency conditions between two background colors. As to the foreground extraction, the boundary between the foreground and the background is detected to recheck the foreground region whose color is same as the background, and the background region whose color is same as the foreground. To detect the region whose color is same as the background, the adjacency conditions with the striped region are utilized. As to the image composition, the process that smoothes the color of the foreground's boundary against the new background is carried out to create natural images. The validity of proposed method is shown through experiments with the foreground objects whose color is same as the background color.