Showing papers by "Tomoo Mitsunaga published in 1995"

AutoKey: human assisted key extraction

Abstract: Key extraction is an inverse problem of finding the foreground, the background, and the alpha from an image and some hints. Although the chromakey solves this for a limited case (single background color), this is often too restrictive in practical situations. When the extraction from arbitrary background is necessary, this is currently done by a time consuming manual task. In order to reduce the operator load, attempts have been made to assist operators using either color space or image space information. However, existing approaches have their limitations. Especially, they leave too much work to operators. In this paper, we present a key extraction algorithm which for the first time, addresses the problem quantitatively. We first derive a partial differential equation that relates the gradient of an image to the alpha values. We then describe an efficient algorithm that provides the alpha values as the solution of the equation. Along with our accurate motion estimation technique, it produces correct alpha values almost everywhere, leaving little work to operators. We also show that a careful design of the algorithm and the data representation greatly improves human interaction. At every step of the algorithm, human interaction is possible and it is intuitive. CR Categories: I.3.3 [Computer Graphics]: Picture / Image Generation; I.4.6 [Image Processing]: Segmentation Edge and feature detection; I.4.7 [Image Processing]: Feature Measurement; I.5.2 [Pattern Recognition]: Design Methodology Feature evaluation and selection. Additional

Image detecting apparatus

Abstract: An image area extracting method for extracting the desired areas from the image accurately and efficiently. The rough boundary area, in which the boundary area is roughly assigned between the desired area and areas other than the desired area, is divided into a plurality of small areas. The area extracting procedure is executed on each small area and the desired area and areas other than the desired area are detected from each small area. The boundary area mask image is formed based on the detection result and the desired area is extracted based on the boundary area mask image. Thus, the desired area can be extracted from the image accurately and efficiently.

Method and device for detecting edge

Abstract: PURPOSE: To improve the precision of edge detection by calculating the edge intensity to detect the picture element group, where the picture element value is steeply changed in comparison with peripheral picture element values, as an edge. CONSTITUTION: A gradient calculation part 11 to which an input picture F in is supplied, a spline curve generation part 12 to which an outline P of contours is supplied, a parameter coordicate generation part 13 which generates a parameter (t) to the spline,curve generation part 12, and an edge intensity calculation part 14 which calculates an edge intensity E in accordance with the output from the gradient calculation part 11 and that from the spline curve generation part 12 are provided. The edge direction of each position in input picture data consisting of variable density data is estimated. The gradient in each position is obtained. The edge intensity calculation part 14 takes information of the estimated edge direction as auxiliary information and calculates the edge intensity E in accordance with this auxiliary information and the gradient, and the picture element group where the picture element value is steeply changed in comparison with peripheral picture element values is detected as an edge. COPYRIGHT: (C)1996,JPO