Abstract: An input SVG file to be processed is accessed. Reusable symbols in the input SVG are identified, e.g., which satisfy a symbol size requirement. A set of symbols are selected from among the identified reusable symbols for conversion to glyphs of a custom binary font, e.g., based on symbol occurrence frequency. A binary font file is created corresponding to set the selected identified symbols in the SVG input file. An SVG output file is created including: binary font glyph definitions corresponding to the converted identified symbols, definitions of symbols from the SVG input file which have not been converted to glyphs and information indicating where the glyphs and symbols, which were not converted, are to be placed on an output display page. The generated SVG output file is a more efficient SVG file than the input SVG file. Different custom binary font files are created for different SVG input pages.

Abstract: Methods and apparatus for managing resource utilization in a distributed system are described. Devices, e.g., servers, which use resources, e.g., processing cores, act as individual policy enforcement points. Individual servers retrieve and maintain local copies of resource lease records which are stored in a centralized data storage system. The individual server compares locally stored lease records to the retrieved lease records to check for any tampering in the centralized data storage and multiple states are supported to take into consideration transitory conditions and/or communications delays. Verification states include, e.g., a Pending Active state and a Pending Inactive State, in addition to an Active state and Inactive state, to delay licensing enforcement to account for centralized storage system eventual consistency delays.

Abstract: Methods and apparatus for determining the skew angle of a digitized form scanned at an angle to the original page are described. The method determines a rotation angle and a boundary rectangle of best fit. Sections of the digital image in the form of thin strips are examined for the boundary between the page and the region of the scanned image beyond the original page. The Hough transform is employed to determined candidate edge line segments for the page from the sets of perimeter points. These line segments are then combined to select the best rectangle enclosing the page, from which the skew angle is determined. The algorithm also determines a rotated bounding box enclosing the page.

Abstract: Methods and apparatus for determining the skew angle of a digitized form scanned at an angle to the original page are described. The method determines a rotation angle and a boundary rectangle of best fit. Sections of the digital image in the form of thin strips are examined for the boundary between the page and the region of the scanned image beyond the original page. The Hough transform is employed to determined candidate edge line segments for the page from the sets of perimeter points. These line segments are then combined to select the best rectangle enclosing the page, from which the skew angle is determined. The algorithm also determines a rotated bounding box enclosing the page.

Abstract: There is provided herein a new method of identifying when a particular hand-drawn selection has been made on, for example, a standardized test form. This method does not require the use of any particular form nor does it use registration marks. It is robust enough to be used when the form is somewhat misaligned on the scanning device. This method utilizes a scanned “blank” form which is then compared with a form containing user markings thereon. As a first step, the user's form is mathematically iteratively aligned with the scanned blank form. As a next step, a fine-scale refinement is applied to each individual “bubble” (i.e., response field) of the user's form to bring that feature into near exact alignment with the same bubble on the blank form. Finally, a quantitative measure of the similarity between the blank and user forms is used to determine whether or not the user has made a mark on the form within that response region.

Abstract: There is provided herein a new method of identifying when a particular hand-drawn selection has been made on, for example, a standardized test form. This method does not require the use of any particular form nor does it use registration marks. It is robust enough to be used when the form is somewhat misaligned on the scanning device. This method utilizes a scanned “blank” form which is then compared with a form containing user markings thereon. As a first step, the user's form is mathematically iteratively aligned with the scanned blank form. As a next step, a fine-scale refinement is applied to each individual “bubble” (i.e., response field) of the user's form to bring that feature into near exact alignment with the same bubble on the blank form. Finally, a quantitative measure of the similarity between the blank and user forms is used to determine whether or not the user has made a mark on the form within that response region.