Abstract: A method for creating a modeling structure for classifying objects in an image comprises converting an image into digital image data; using a processor, simplifying the digital image data; using the processor, isolating objects in the simplified digital image data; using the processor, creating graphs of the isolated objects, the graphs comprising vertices and edges; using the processor, converting the graphs into representative graph data structures, the graph data structures comprising a database key based on the vertices and edges.

Abstract: A method for generating architectural design requirements for a building structure is disclosed. A schematic drawing file of the building structure is loaded. The building type for the building structure is designated. A topology mask identifying the functional zones demarcated by the schematic drawing is created over the schematic drawing. Architectural design standards that are specific to the building type designated are applied to each of the identified functional zones to generate the architectural design requirements for the building structure. The architectural design standards being stored in a relational database.

Abstract: A method for recognizing a character string on a static document is disclosed. The character string is extracted from the static document. The character string is converted into a representative character string graph. The common embedded isomorphic graphs are extracted from the representative character string graph. Each of the common embedded isomorphic graphs extracted are converted into digital ink files. The character string associated with each of the digital ink files are identified using a dynamic recognition system.

Abstract: A biometric handwriting identification system converts characters and a writing sample into mathematical graphs. The graphs comprise enough information to capture the features of handwriting that are unique to each individual. Optical character recognition (OCR) techniques can then be used to identify these features in the handwriting sample so that drafts from two different samples can be aligned to compare to determine if the features in the writing sample correlate with each other.

Abstract: A data capture and mining method which enables identification of characters and words through their visible patterns. Specifically, a data capture and mining method involves searching a scanned image using isomorphic, graphical pattern matching techniques that eliminate both the need to convert imaged writing to electronic format through, e.g., OCR and the subsequent need to convert the electronic text into English.

Abstract: A detection and tracking method that enables an objective determination of changes in handwriting with the passage of time and progress of medical conditions which affect fine motor skills. Specifically, a detection and tracking method which precisely describes a handwriting sample as a plurality of features which become indicators of a medical disorder affecting fine motor skills. The indicators are obtained and characterized using analytical and statistical techniques resulting in the development of diagnostic tools for detection and management of that disorder.