Abstract: A processor measures skew of lines in an image by obtaining a first, coarse approximation to skew direction and then using the first approximation to obtain a second, fine approximation that is more precise than the first. A third, even more precise approximation can be obtained using the second approximation, and further successive approximations can be similarly obtained. In an image of text, the first approximation can be obtained by finding the direction in which characters are closest together, since intercharacter distances are typically smaller than interline distances. This direction can be determined by measuring distances from selected pixels at edges of connected components across white pixels to edges of other connected components. The measured distances in each direction can be combined to obtain a central value for the direction, such as an average. The central values form a profile indicating central value as a function of direction.

Abstract: A method for determining the boundaries of a symbol or word string within an image, including the steps of determining page orientation, isolating symbol strings from adjacent symbol strings, establishing a set of boundaries or references with respect to which measurements about, or further processing of, the symbol string may be made.

Abstract: A device for creating and displaying a graph describing the dynamic of a game. The graph is created by displaying the a curve representing the score of the game at significant moments in the process of the game. This is superimposed upon information describing these significant moments. Markers that connect these significant instances with the score are also shown. These graphical forms may be displayed in an animated production.

Abstract: An image is analyzed by random or pseudorandom sampling. Information about attributes such as skew, typeface, and character size and spacing is obtained by measuring a characteristic at a number of sampled locations and combining the results to obtain a measure of the characteristic for the image. The number of sampled locations is smaller than the number of locations in the image, but is large enough to achieve a degree of statistical significance. The sampled locations can be selected by obtaining a random or pseudorandom number indicating a candidate location and then applying a criterion to determine whether the candidate location is an appropriate starting point for the measurement. For example, the criterion can be that the location must be a pixel within a character or must be a pixel of a given color at an edge. The measurement can indicate a distance from each sampled location in each of a number of directions, such as the distance to an edge.

Abstract: A method for determining the boundaries of a symbol or word string within an image, including the steps of determining page orientation, isolating symbol strings from adjacent symbol strings, establishing a set of boundaries or references with respect to which measurements about, or further processing of, the symbol string may be made.

Abstract: Dominant typeface, including point size, of text in an image is identified by measuring distances across connected components in each of plural directions to obtain distribution data. The distribution data indicate a distribution of distances across connected components in each direction for the image. The distribution data are then used to obtain typeface data indicating the dominant typeface of characters in the text. Distance can be measured from each of a set of pixels that are inside or on edges of connected components to an edge of a connected component. The distances for each direction can be combined, such as by obtaining an average or other measure of central value, so that the combined distances indicate the distribution of distances in the direction. The distribution data can be used to form a profile that can be compared or clustered with other profiles to identify similar profiles or to find a matching profile. Skew can be obtained and used in forming profiles that are independent of skew.

Abstract: Characteristics of images such as skew of lines of text or dominant typeface of characters are detected by producing distance data. Distance data is produced for each of a number of starting pixels within an image. Each starting pixel meets a criterion, such as an edge pixel or a pixel inside a connected component. Each starting pixel's distance data indicates the distance in each of a number of directions from the starting pixel to another pixel at which the image meets another criterion. For example, to detect skew of lines of text, the distance data can indicate distance from a starting pixel at an edge across white pixels to another edge. To detect dominant typeface, the distance data can indicate distance from a starting pixel at an edge or inside a connected component across black pixels to another edge.