Abstract: A background predicting process is disclosed which determines, for each designated line of input image data, whether or not the pixels of a particular line are the edge portion of a line drawing. The process finds the brightness value for each pixel, excluding the effects of the brightness of the edge portion in the line drawing (step s1). Next, a background prediction modifying process is accomplished which determines whether or not the effects of a line drawing portion other than the edge are included in the brightness value of each pixel in the line being processed. When the effects of a line drawing portion other than the edge are included, the process finds the brightness value of each pixel excluding this effect (step s2). A background modification is then conducted by modifying the brightness so as to achieve a desired brightness value on the basis of the brightness value of each pixel obtained by this background prediction modifying process (step s3).

Abstract: In an artificial intelligence system for image recognition, a global image of an object is input from a camera or other optical pick-up device, and is processed in a global image processing means, which performs analytical processing on the global image by extracting global characteristics of the input image and evaluating consistency of the extracted global characteristics. Simultaneously, the image data is processed in a local image processing means which undertakes analytical processing on a plurality of local images defining local portions of the image to be recognized. The local image processing means is constructed by plural modules, each further defined by sub-modules, which conduct respective analyses corresponding to local images having characteristics useful in recognizing the global image, wherein each local processor extracts characteristics of an input local image and evaluates consistency of the extracted characteristic with the object to be recognized.

Abstract: A system and method for rapidly obtaining information about the suitability of terrain to meet concealment or visibility objectives, such as might be needed for military planning or for determining placement of relay antennas in a cellular communication system, is disclosed. The disclosed system precomputes heuristic visibility fields for a geographic area, then uses the precomputed heuristic visibility fields to rapidly determine points on a map that will provide the desired characteristics of exposure or concealment in response to a query.

Abstract: There is described a method for determining the relative location between a rectangle and a polygon. First, a box that bounds the polygon is created. An outside indicator is returned if the rectangle is outside the box. An intersect indicator is returned if the box is entirely inside the rectangle. If an odd/even fill process is in use then first the intersect indicator is returned if the rectangle intersects with the polygon or if a subpath bounding box is entirely inside the rectangle. Finally, if the location of the rectangle has not yet been returned, the location of a single point of the rectangle is returned. If a non-zero winding fill process is in use, first, the intersect indicator is returned if at least one corner of the rectangle is in a different side of the polygon than remaining corners of the rectangle.

Abstract: The invention aims at recognition of a handwritten input character on-line with quite high accuracy. The method of on-line handwritten input character recognition of the invention is characterized in that ordinary strokes and transition strokes and/or start-end (s-e) strokes of a handwritten input character sampled on-line are compared with ordinary strokes and transition strokes and/or s-e strokes of dictionary's characters previously registered in a dictionary and the character corresponding to the handwritten input character is recognized on the basis of the result of the comparison. Otherwise, when the dictionary's character most similar to the input character corresponds to a preset character, the handwritten input character is identified by using characteristic features of the corresponding character.

Abstract: A method and apparatus for locating geometric shapes or edges thereof in data collection symbols initially samples and stores an image of light reflected from the symbol. Thereafter, two routines are performed. A first routine performs low level vision processing by identifying linked points along edges, lines, curves or within shapes. At least one of three distortion compensating subroutines compensate for blocking, breaking, gaps or other severe distortions affecting shapes in the stored image. Under a first subroutine, an edge of a shape is tracked until a stopping condition occurs, at which point the shape is crossed so as to continue tracking on an opposite edge. Under a second subroutine, previously collected linear curve information is used to identify a jump point to continue tracking following a stopping condition. Under a third subroutine, mathematical morphology techniques are employed to close gaps or move blockage in shapes in the stored image.

Abstract: An information input method and interface, which can easily be operated without direct awareness of hardware, are provided. Image recognition is performed with an image recognition unit on image information obtained from imaging a target pattern on an object surface and an access indication pattern created by a user. The input patterns are created with an image pickup unit. The target pattern is associated with corresponding information stored in a storage unit. An access indication input which specifies a subset of the information is generated by performing image recognition on the access indication pattern. A control operation corresponding to the access indication input is performed in response to the access indication input by a control unit.

Abstract: Matching between a reference image and an input image is performed without relying on specific elements such as line segments or tables. An edge image is generated from the reference image and divided into small blocks, and search range and search priority of each small block are determined and stored in a storage device. When an input image is input, an edge image thereof is generated. The small blocks in the reference image are retrieved in order of priority, and matching with the input image is judged. When the corresponding position of one small block is determined, the search range and search priority for other small blocks not yet judged for matching are updated on the basis of the determined corresponding position.

Abstract: An imaging subsystem for a printer is configured to support multiple printer personalities. The imaging subsystem has an integrated display list that is accessed and used by all of the printer personalities. The printer implements a display list builder tool that assists each personality in posting its objects to the display list.