Abstract: A method of embedding watermark data into a two-colour (binary) image includes dividing the image into blocks and assessing the suitability of each block to embed a bit of watermark data by assessing whether or not the flipping of a defined pixel in each block affects the visual attributes of said block in manner to be perceptible by the human eye. Data is only embedded in those blocks determined to be suitable for data embedding, by flipping the defined pixel, as required. A recipient of the document may similarly assess which blocks contain watermark data, by assessing the suitability of each block in the document to embed such data. Conveniently, watermark data may be extracted without further information about the data's location within a document.

Abstract: A biometric based system with advanced security and privacy characteristics for the verification of a person's identity using neural net engine simulation software code and neural net weights obtained from a computer enrollment system and ported into any electronic device with an embedded microprocessor and memory. The neural net structure has both inter and intra layer connections of all nodes.

Abstract: An improved system and method for building security and occupant safety wherein a digital image of plan view of a selected floor of a building is prepared from a physical drawing. The digital image shows the substantial architectural features of the building, including external walls (10) and internal walls (12). In the digital image, the building floor is divided into several zones (14) and each of the zones is broken into segments (16). Each of the segments (16) is identified by alpha/numeric characters or other symbols by which emergency responders or other building occupants can navigate the building.

Abstract: In step S1, image data obtained by imaging is input to an image input unit (1). In step S2, the diagnosis result obtained by a doctor using the image data obtained by imaging is input as diagnosis information to a diagnosis information input unit (2). In step S3, a keyword table (7) is searched for a keyword input to the diagnosis information input unit (2) or a diagnosis information analyzing unit (3). In step S4, a parameter determining unit (5) selects an initial value parameter used in an image search unit (4) from an initial value table (8) on the basis of the input keyword. In steps S5 and S6, the image search unit (4) determines the optimization degree of the selected parameter by applying the parameter to the input image on the basis of the area or connectivity of a morbid region, and also extracts a morbid region by using a general computer aided diagnosis technique.